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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220613T180000
DTEND;TZID=America/New_York:20220613T200000
DTSTAMP:20260416T082716
CREATED:20220606T210130Z
LAST-MODIFIED:20220613T205109Z
UID:10000544-1655143200-1655150400@www.ieeetoronto.ca
SUMMARY:C# Development 101 (06 out of 06)
DESCRIPTION:Join the IEEE Toronto Magnetics Chapter and Women in Engineering for a C# Development workshop. \nSpeaker(s): Reza Dibaj \nRegister: https://events.vtools.ieee.org/m/314674
URL:https://www.ieeetoronto.ca/event/c-development-101-06-out-of-06/
LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/314674
CATEGORIES:Magnetics,Women in Engineering
ORGANIZER;CN="Reza Dibaj":MAILTO:reza.dibaj@ieee.org
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220613T160000
DTEND;TZID=America/New_York:20220613T180000
DTSTAMP:20260416T082716
CREATED:20220606T205950Z
LAST-MODIFIED:20220613T205108Z
UID:10000542-1655136000-1655143200@www.ieeetoronto.ca
SUMMARY:Python Development 101 (06 out of 06)
DESCRIPTION:Python Development 101 continues with the IEEE Toronto Magnetics chapter and WIE. \nSpeaker(s): Reza Dibaj \nRegister: https://events.vtools.ieee.org/m/314669
URL:https://www.ieeetoronto.ca/event/python-development-101-06-out-of-06/
LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/314669
CATEGORIES:Magnetics,Women in Engineering
ORGANIZER;CN="Reza Dibaj":MAILTO:reza.dibaj@ieee.org
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220606T180000
DTEND;TZID=America/New_York:20220606T200000
DTSTAMP:20260416T082716
CREATED:20220606T210046Z
LAST-MODIFIED:20220606T210046Z
UID:10000543-1654538400-1654545600@www.ieeetoronto.ca
SUMMARY:C# Development 101 (05 out of 06)
DESCRIPTION:Join the IEEE Toronto Magnetics Chapter and Women in Engineering for a C# Development workshop. \nSpeaker(s): Reza Dibaj \nRegister: https://events.vtools.ieee.org/m/314673
URL:https://www.ieeetoronto.ca/event/c-development-101-05-out-of-06/
LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/314673
CATEGORIES:Magnetics,Women in Engineering
ORGANIZER;CN="Reza Dibaj":MAILTO:reza.dibaj@ieee.org
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220606T160000
DTEND;TZID=America/New_York:20220606T180000
DTSTAMP:20260416T082716
CREATED:20220606T205930Z
LAST-MODIFIED:20220606T205930Z
UID:10000541-1654531200-1654538400@www.ieeetoronto.ca
SUMMARY:Python Development 101 (05 out of 06)
DESCRIPTION:Python Development 101 continues with the IEEE Toronto Magnetics chapter and WIE. \nSpeaker(s): Reza Dibaj \nRegister: https://events.vtools.ieee.org/m/314668
URL:https://www.ieeetoronto.ca/event/python-development-101-05-out-of-06/
LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/314668
CATEGORIES:Magnetics,Women in Engineering
ORGANIZER;CN="Reza Dibaj":MAILTO:reza.dibaj@ieee.org
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220603T160000
DTEND;TZID=America/New_York:20220603T180000
DTSTAMP:20260416T082716
CREATED:20220606T205843Z
LAST-MODIFIED:20220606T205843Z
UID:10000540-1654272000-1654279200@www.ieeetoronto.ca
SUMMARY:C# Development 101 (04 out of 06)
DESCRIPTION:C# Development 101 continues with the Magnetics chapter and WIE. \nSpeaker(s): Reza Dibaj \nRegister: https://events.vtools.ieee.org/m/314672
URL:https://www.ieeetoronto.ca/event/c-development-101-04-out-of-06/
LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/314672
CATEGORIES:Magnetics,Women in Engineering
ORGANIZER;CN="Reza Dibaj":MAILTO:reza.dibaj@ieee.org
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220530T160000
DTEND;TZID=America/New_York:20220530T180000
DTSTAMP:20260416T082716
CREATED:20220606T205746Z
LAST-MODIFIED:20220606T205746Z
UID:10000539-1653926400-1653933600@www.ieeetoronto.ca
SUMMARY:Python Development 101 (04 out of 06)
DESCRIPTION:Python Development 101 continues with the IEEE Toronto Magnetics chapter and WIE. \nSpeaker(s): Reza Dibaj \nRegister: https://events.vtools.ieee.org/m/314667
URL:https://www.ieeetoronto.ca/event/python-development-101-04-out-of-06/
LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/314667
CATEGORIES:Magnetics,Women in Engineering
ORGANIZER;CN="Reza Dibaj":MAILTO:reza.dibaj@ieee.org
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220527T180000
DTEND;TZID=America/New_York:20220527T200000
DTSTAMP:20260416T082716
CREATED:20220526T185938Z
LAST-MODIFIED:20220528T100255Z
UID:10000533-1653674400-1653681600@www.ieeetoronto.ca
SUMMARY:Data Visualization using Tableau
DESCRIPTION:Join the IEEE Toronto Magnetics Chapter and Women In Engineering for this two-hour data visualization workshop! \nVisualization is an indispensable part of today’s data science\, and Tableau is one of the most common tools for visualization. In a two-hour workshop technical presentation\, we will quickly go through the fundamentals of Tableau visualization. \nSpeaker(s): Dr. Reza Dibaj \nVirtual: https://events.vtools.ieee.org/m/315202
URL:https://www.ieeetoronto.ca/event/data-visualization-using-tableau/
LOCATION:Virtual: https://events.vtools.ieee.org/m/315202
CATEGORIES:Magnetics,Women in Engineering
ORGANIZER;CN="Reza Dibaj":MAILTO:reza.dibaj@ieee.org
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220527T160000
DTEND;TZID=America/New_York:20220527T180000
DTSTAMP:20260416T082716
CREATED:20220606T204156Z
LAST-MODIFIED:20220606T204156Z
UID:10000537-1653667200-1653674400@www.ieeetoronto.ca
SUMMARY:C# Development 101 (03 out of 06)
DESCRIPTION:IEEE Toronto’s Magnetic Chapter and WIE C# Development 101 continues. \nSpeaker(s): Reza Dibaj \nRegister: https://events.vtools.ieee.org/m/314671
URL:https://www.ieeetoronto.ca/event/c-development-101-03-out-of-06/
LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/314671
CATEGORIES:Magnetics,Women in Engineering
ORGANIZER;CN="Reza Dibaj":MAILTO:reza.dibaj@ieee.org
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220514T180000
DTEND;TZID=America/New_York:20220514T190000
DTSTAMP:20260416T082716
CREATED:20220518T191134Z
LAST-MODIFIED:20220524T100553Z
UID:10000526-1652551200-1652554800@www.ieeetoronto.ca
SUMMARY:Visualization Techniques in Cancer Level Detection System – Students’ Research in ML and DL at Durham College
DESCRIPTION:Cancer is one of the leading causes of death in the world. To tackle this menace\, pathologists need a faster and better way to diagnose their patients. This led the team to work on evaluating different machine learning models to find out which model works best in accurately predicting the level of cancer development in a patient. In the course of the project\, we explored different features of our datasets with the help of visualization tools like tableau and python data visualization libraries to enable us to see the relationship between each feature and the level of cancer in a patient. We also\, in the end\, evaluated the performance of each algorithm using python visualization tools to better understand which algorithms performed the best. \nSpeaker(s): Rakesh Pattanayak\, Chisom Nnabuisi\, Dhruv Mistry\, Kar Chun Kan\, Shanuka Rathnayake \nRegister: https://events.vtools.ieee.org/m/313212
URL:https://www.ieeetoronto.ca/event/visualization-techniques-in-cancer-level-detection-system-students-research-in-ml-and-dl-at-durham-college/
LOCATION:toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/313212
CATEGORIES:Magnetics,Women in Engineering
ORGANIZER;CN="Reza Dibaj":MAILTO:reza.dibaj@ieee.org
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220513T190000
DTEND;TZID=America/New_York:20220513T210000
DTSTAMP:20260416T082716
CREATED:20220518T191548Z
LAST-MODIFIED:20220524T100553Z
UID:10000528-1652468400-1652475600@www.ieeetoronto.ca
SUMMARY:C# Development 101 - Introduction (01 out of 06)
DESCRIPTION:Join the IEEE Toronto Magnetics Chapter and Women in Engineering for a C# Development workshop. \nSpeaker(s): Reza Dibaj \nRegister: https://events.vtools.ieee.org/m/314229
URL:https://www.ieeetoronto.ca/event/c-development-101-introduction-01-out-of-06/
LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/314229
CATEGORIES:Magnetics,Women in Engineering
ORGANIZER;CN="Reza Dibaj":MAILTO:reza.dibaj@ieee.org
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220513T180000
DTEND;TZID=America/New_York:20220513T190000
DTSTAMP:20260416T082716
CREATED:20220518T191404Z
LAST-MODIFIED:20220524T100553Z
UID:10000527-1652464800-1652468400@www.ieeetoronto.ca
SUMMARY:Visualization Techniques to Demonstrate the Cause of Climate Changes – Students’ Research in ML and DL at Durham College
DESCRIPTION:We might always be confused about climate and weather\, and what is the difference between each other? Weather refers to the day-to-day temperature and atmospheric conditions\, whereas climate is the average weather in a specific region over a long period. The simplest way to describe climate is to analyze the average temperature and precipitation over time. Climate change relates to the shift in the average conditions such as average temperature and rainfall in a region over a period. Global climate change describes the average long-term changes over the entire Earth. Global warming\, Rise in sea level\, and Shrinking Mountain glaciers are a few of the adverse effects of climatic changes. Greenhouse gases are the prominent factors for the rising temperature\, which is the main factor contributing to global warming. Among the greenhouse gases\, carbon dioxide is the main factor that traps the heat in the atmosphere\, which makes an increase in the overall temperature that can affect lives on Earth. Earth’s temperature has risen by 0.14° F (0.08° C) per decade since 1880\, and the rate of warming over the past 40 years is more than twice that: 0.32° F (0.18° C) per decade since 1981. We will try to find the possible reasons for climatic changes and the factors that contributed to the current situation. Moreover\, we will consider greenhouse gas emissions and their harmful effects on climatic changes\, different countries’ contributions to this global problem\, and measures taken by officials to reduce its impact. \nSpeaker(s): Neenu Markose\, Akhil Mathew \nRegister: https://events.vtools.ieee.org/m/313211
URL:https://www.ieeetoronto.ca/event/visualization-techniques-to-demonstrate-the-cause-of-climate-changes-students-research-in-ml-and-dl-at-durham-college/
LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/313211
CATEGORIES:Magnetics,Women in Engineering
ORGANIZER;CN="Maryam Davoudpour":MAILTO:maryam.davoudpour@ieee.org
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220513T160000
DTEND;TZID=America/New_York:20220513T170000
DTSTAMP:20260416T082716
CREATED:20220518T191706Z
LAST-MODIFIED:20220524T100553Z
UID:10000529-1652457600-1652461200@www.ieeetoronto.ca
SUMMARY:Data Analysis and Visualization Techniques in Supermarket Sales – Students’ Research in ML and DL at Durham College
DESCRIPTION:We will explain the significance of visualization charts in narratives and presentations with a brief explanation of chart appropriateness\, noise reduction\, and decluttering aspects. We will continue by shedding light on the necessity of good communication tactics\, criteria and approaches for improving visuals and narrative techniques. Moreover\, applying the above concepts\, we will explain how to use tableau as a software application to produce visuals to perform the superstore sales data analysis. Furthermore\, we will analyze supermarket sales data\, using appropriate charts for six product lines\, customer types\, and payment methods. We will use six categories of products\, i.e. Electronic accessories\, Food & Beverages\, Health & Beauty\, Home & Lifestyle\, and Sports & travelling products\, to carry out the analysis. We will emphasize the research’s target audience by providing pertinent insights and making recommendations. \nSpeaker(s): Minu Ahlawat\, Megha Garg\, Dwij Dua & Taxil Savani \nRegister: https://events.vtools.ieee.org/m/313209
URL:https://www.ieeetoronto.ca/event/data-analysis-and-visualization-techniques-in-supermarket-sales-students-research-in-ml-and-dl-at-durham-college/
LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/313209
CATEGORIES:Magnetics,Women in Engineering
ORGANIZER;CN="Reza Dibaj":MAILTO:reza.dibaj@ieee.org
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220512T160000
DTEND;TZID=America/New_York:20220512T170000
DTSTAMP:20260416T082716
CREATED:20220518T191802Z
LAST-MODIFIED:20220524T100552Z
UID:10000530-1652371200-1652374800@www.ieeetoronto.ca
SUMMARY:Visualization Techniques in Text Summarization of Online Transcripts – Students’ Research in ML and DL at Durham College
DESCRIPTION:Text summarization is a method for generating a summary of long texts by focusing on the sections that contain essential information while keeping the overall meaning intact. Its goal is to reduce the size of long documents\, which would be difficult and expensive to process manually. With the current explosion of data circulating in digital space\, particularly unstructured textual data\, there is a need to build tools that allow people to extract insights from it. Taking notes is a popular practice for many people employed in situations where it is essential to keep track of what is said\, such as during an online lecture. The art of note-taking does not entail taking down every single word stated but rather broad summaries of what is covered. Making succinct yet informative summaries is the key to successful note-taking. In this seminar\, we will be discussing how we have used visualization and data storytelling techniques in our project to make informed decisions. This project aims to address the difficulties of note-taking by building an application that produces notes based on the transcripts generated by the Automatic Speech Recognition (ASR) technology of the meeting platforms. We relied on visualization concepts for three major decisions that would define our project as a whole. These decisions are the choice of online meeting platform\, preference of text summarization model and the messaging platform choice. \nSpeaker(s): Manoj Varma Alluri\, Navaneeth Jawahar\, Sharath Kumar Prabhu\, Jeel Jani \nRegister: https://events.vtools.ieee.org/m/313207
URL:https://www.ieeetoronto.ca/event/visualization-techniques-in-text-summarization-of-online-transcripts-students-research-in-ml-and-dl-at-durham-college/
LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/313207
CATEGORIES:Magnetics,Women in Engineering
ORGANIZER;CN="Reza Dibaj":MAILTO:reza.dibaj@ieee.org
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220512T140000
DTEND;TZID=America/New_York:20220512T150000
DTSTAMP:20260416T082716
CREATED:20220518T191856Z
LAST-MODIFIED:20220524T100552Z
UID:10000531-1652364000-1652367600@www.ieeetoronto.ca
SUMMARY:Fraud Data Analysis & Exploration using Interactive Tableau Dashboard – Students’ Research in ML and DL at Durham College
DESCRIPTION:Credit card fraud detection is an ever-growing problem in today’s financial market with a rapid increase in plastic card usage worldwide. According to the Nelson report\, by 2027\, financial service providers are expected to take a $40 billion hit globally in credit card losses\, a significant increase compared to previous years. Hence\, data-driven decisions can largely help in mitigating that risk. We chose this topic to deep dive into different aspects of Fraud Data Analysis & Exploration using Interactive Tableau Dashboard. Tableau dashboards can be very powerful in driving data-driven decisions. We created an interactive dashboard to help stakeholders or less technical people to drive insights\, understand data better\, and help in business decisions making. The interactive feature helps users to add filters as per their needs and understand the data in a way they want to analyze. Our dashboard is dynamic and would be updated when several filters are applied together. Multiple filters can be added to multiple charts at the same time. These charts are intuitive which makes even new users easily interact and understand the data. \nSpeaker(s): Priyanka Singh & Devy Ratnasari \nRegister: https://events.vtools.ieee.org/m/313201
URL:https://www.ieeetoronto.ca/event/fraud-data-analysis-exploration-using-interactive-tableau-dashboard-students-research-in-ml-and-dl-at-durham-college/
LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/313201
CATEGORIES:Magnetics,Women in Engineering
ORGANIZER;CN="Reza Dibaj":MAILTO:reza.dibaj@ieee.org
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220507T180000
DTEND;TZID=America/New_York:20220507T190000
DTSTAMP:20260416T082716
CREATED:20220505T200912Z
LAST-MODIFIED:20220507T074848Z
UID:10000361-1651946400-1651950000@www.ieeetoronto.ca
SUMMARY:Alert on Mask Detection System – Students Research in ML and DL at Durham College
DESCRIPTION:As a result of the fast development and spread of the COVID-19 pandemic throughout the world\, people’s everyday lives have been severely disrupted in recent times. One proposal for controlling the epidemic is to make individuals wear face masks in public. As a result\, we require face detection systems that are both automated and efficient for such enforcement. We propose a face mask identification model for static and real-time videos in this research\, and the pictures are classified as “with mask” or “without a mask.” The model uses a Kaggle dataset to train and test. The collected data set contains over 10\,000 images (considering 5\,000 with mask and similarly 5\,000 without) and has a 98 percent performance accuracy rate. The proposed model is computationally efficient and precise compared to Haar-Cascade & ANN. The application of this research are various\, including digitized scanning tool in schools\, hospitals\, banks\, airports\, and many other public or commercial locations. \nSpeaker(s): Henil Shah\, Neenu Markose \nRegister: https://events.vtools.ieee.org/m/312341
URL:https://www.ieeetoronto.ca/event/alert-on-mask-detection-system-students-research-in-ml-and-dl-at-durham-college/
LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/312341
CATEGORIES:Magnetics,Women in Engineering
ORGANIZER;CN="Reza Dibaj":MAILTO:reza.dibaj@ieee.org
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220506T180000
DTEND;TZID=America/New_York:20220506T190000
DTSTAMP:20260416T082716
CREATED:20220502T172656Z
LAST-MODIFIED:20220507T074847Z
UID:10000357-1651860000-1651863600@www.ieeetoronto.ca
SUMMARY:Cancer Level Detection System – Students Research in ML and DL at Durham College
DESCRIPTION:Cancer ranks as a leading cause of death and an important barrier to increasing life expectancy everywhere. According to available data\, lung cancer contributes the most to cancer deaths. Also\, according to available data\, those diagnosed early have a 50 percent chance of survival over those diagnosed with late-stage cancer. It means that early detection is paramount to the survival of a lung cancer patient\, leading to a reduction in the number of cancer deaths. We\, therefore\, evaluated six different machine learning algorithms to see which one performed optimally in accurately predicting the level of lung cancer development in a patient. We considered various parameters when choosing the dataset for this evaluation as the pathogenesis of lung cancer involves a combination of intrinsic factors and exposure to environmental carcinogens. We also considered varying the features in our data\, categorizing them under diagnostic risk factors (age\, gender\, alcohol use\, air pollution\, balanced diet\, obesity\, smoking\, passive smoker) and symptoms (fatigue\, weight loss\, shortness of breath\, swallowing difficulty\, frequent cold\, dry cough) and the inferences we drew from this indicated that those that have the symptom features prior to diagnosis had the highest chance of being diagnosed with a high level of cancer. The final results of our evaluation showed that the best levels of predictions on new data were achieved by optimized Random Forest\, KNN\, and SVM models. \nSpeakers: Rakesh Pattanayak\, Chisom Nnabuisi\, Dhruv Mistry\, Kar Chun Kan\, Shanuka Rathnayake \nRegister: https://events.vtools.ieee.org/m/312340
URL:https://www.ieeetoronto.ca/event/cancer-level-detection-system-students-research-in-ml-and-dl-at-durham-college/
LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/312340
CATEGORIES:Magnetics,Women in Engineering
ORGANIZER;CN="Reza Dibaj":MAILTO:reza.dibaj@ieee.org
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220503T180000
DTEND;TZID=America/New_York:20220503T190000
DTSTAMP:20260416T082716
CREATED:20220502T171646Z
LAST-MODIFIED:20220504T073258Z
UID:10000346-1651600800-1651604400@www.ieeetoronto.ca
SUMMARY:DDoS Detection System – Students Research in ML and DL at Durham College
DESCRIPTION:The research goal is to implement different machine learning algorithms to detect any DDoS (Distributed Denial of Service) attacks using the UNSW-NB15 dataset. We started by going through the data description and finding null values in our features. After that we dropped the ‘id’ column. \nWe have used the UNSW-15 dataset for AI-based DDOS detection systems. \nThe UNSW-15 dataset has a hybrid of the real modern normal and the contemporary synthesized attack activities of the network traffic. It contains different attacks\, including DoS\, worms\, Backdoors etc. The raw network packets of the UNSW-NB 15 datasets are created by the IXIA Perfect Storm tool in the Cyber Range Lab of the Australian Centre for Cyber Security (ACCS) for generating a hybrid of real modern normal activities and synthetic contemporary attack behaviours. We incorporated different feature selection methods for dropping insignificant features followed by the implementation of 6 classification algorithms\, namely Naive Bayes\, Random Forest\, Decision Tree\, KNN\, Logistic Regression and SVM. \nSpeaker(s): Minu Ahlawat\, Dwij Dua\, Megha Garg\, Taxil Savani \nRegister: https://events.vtools.ieee.org/m/312339
URL:https://www.ieeetoronto.ca/event/ddos-detection-system-students-research-in-ml-and-dl-at-durham-college/
LOCATION:toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/312339
CATEGORIES:Magnetics,Women in Engineering
ORGANIZER;CN="Reza Dibaj":MAILTO:reza.dibaj@ieee.org
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220501T180000
DTEND;TZID=America/New_York:20220501T190000
DTSTAMP:20260416T082716
CREATED:20220502T171452Z
LAST-MODIFIED:20220502T171549Z
UID:10000525-1651428000-1651431600@www.ieeetoronto.ca
SUMMARY:Sentiment Analysis on Twitter Data – Students Research in ML and DL at Durham College
DESCRIPTION:The rise of digitalization and the advent of social media and e-commerce have generated an abundance of data than before. Natural Language Processing (NLP) is a significant branch of artificial intelligence that helps the machine interpret human languages and perform the desired task by analyzing the semantics\, content\, and pattern. Sentiment analysis is the most common technique in Natural Language Processing used to determine the underlying sentiments of a text. This technique is currently in place for different Business Organizations to analyze their brand’s market value\, brand reputation\, and customer perception of new brand/new change. Businesses use social media channels to cater to their customer service\, and people use social media to express/share their wide range of opinions or experiences about a product/brand. These opinions and experiences reflect the real-time sentiments of a customer. Sentiment analysis will help businesses designing an effective marketing campaign\, better customer satisfaction\, boost sales\, help improve customer experience\, understand customer perception to change and the brand’s market reputation. The customer views expressed on Twitter\, Facebook\, and other online forums are forming the base of customer strategy for brands worldwide. Businesses are opting to shift their traditional customer feedback analysis method to text classification since people prefer to post the genuine reviews on the internet. Analyzing the underlying sentiments in the text will help the business to understand their customers’ voices and their brand reputation in the market in real-time. Sentiment analysis will help the businesses designing an effective marketing campaign\, better customer satisfaction\, boost sales\, help improve customer experience\, understand customer perception to change and the brand’s market reputation. Twitter sentiment analysis aims to classify text into positive/negative based on its underlying semantics. \nSpeaker(s): Akhil Mathew\, Anmol Wadera\, Deepan Ellenti Padmanabhan\, Saketh Vemula\, Sivaramakrishna Malakalapalli \nRegister: https://events.vtools.ieee.org/m/312338
URL:https://www.ieeetoronto.ca/event/sentiment-analysis-on-twitter-data-students-research-in-ml-and-dl-at-durham-college/
LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/312338
CATEGORIES:Magnetics,Women in Engineering
ORGANIZER;CN="Reza Dibaj":MAILTO:reza.dibaj@ieee.org
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220428T180000
DTEND;TZID=America/New_York:20220428T190000
DTSTAMP:20260416T082716
CREATED:20220425T202839Z
LAST-MODIFIED:20220429T070737Z
UID:10000524-1651168800-1651172400@www.ieeetoronto.ca
SUMMARY:Text Summarization of Transcripts from Online Meetings – Students Research in ML and DL at Durham College
DESCRIPTION:Text Summarization is a technique for generating a concise and precise summary of voluminous texts while focusing on the sections that convey useful information without losing the overall meaning. It aims to transform lengthy documents into shortened versions\, which could be difficult and costly to undertake if done manually. With the current explosion of data circulating in digital space\, primarily unstructured textual data\, there is a need to develop tools that allow people to get insights from them quickly. In situations where it is essential to keep track of what is being spoken\, such as during an online lecture\, taking notes is a popular activity used by many. The art of notetaking does not involve making notes of every single word that is spoken but comprehensive outlines of what is discussed. The key to good notetaking lies in making concise yet informative summaries. In this seminar\, we will be discussing how we have tried to address the difficulties of notetaking by building an application that produces notes based on transcripts generated by the Automatic Speech Recognition (ASR) technology of the meeting platforms. We experimented with six summarization models for this application\, including transformer-based models pre-trained on large corpora. The datasets used for this application are the transcripts dataset acquired from online meeting platforms and the Extreme Summarization (XSum) dataset. We evaluated the models using Rouge metrics (Rouge-1\, Rouge-2\, and Rouge-L) and selected the best-performing model as the final model. We have built a bot that utilizes Telegram’s API and shares the generated summaries via group chat with the users. \nSpeaker(s): Manoj Varma Alluri\, Navaneeth Jawahar\, Sharath Kumar Prabhu\, Jeel Jani\, Shravya Sandupata\nToronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/312337
URL:https://www.ieeetoronto.ca/event/text-summarization-of-transcripts-from-online-meetings-students-research-in-ml-and-dl-at-durham-college/
LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/312337
CATEGORIES:Magnetics,Women in Engineering
ORGANIZER;CN="Reza Dibaj":MAILTO:reza.dibaj@ieee.org
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220427T180000
DTEND;TZID=America/New_York:20220427T190000
DTSTAMP:20260416T082716
CREATED:20220425T202533Z
LAST-MODIFIED:20220429T070736Z
UID:10000522-1651082400-1651086000@www.ieeetoronto.ca
SUMMARY:Credit Card Fraud Detection – Students Research in ML and DL at Durham College
DESCRIPTION:With the new trend of Online Shopping and Online Platforms for transactions\, the number of Credit Card based transactions increased tremendously. However\, there have been a lot of cases where illegal use of Debit/Credit Cards for making Fraudulent Transactions. Credit card companies have been paying a lot of attention to providing the best service for their customers by having process enhancements and pro-actively looking into transactions before making them through. Global financial losses related to payment cards are estimated to reach $34.66 billion in 2022\, according to The Nilson Report\, a newsletter that tracks the payment industry. Related to the negative impacts of credit card fraud activities\, and financial and product losses\, it’s easy for merchants and users to feel victimized and helpless. Machine Learning Models can work well in detecting such Fraudulent actions when they are trained on a large quantity of historical data and then fine-tuned depending on validation and evaluation metrics. \nSpeaker(s): Priyanka Singh\, Devy Ratnasari\, Gopika Shaji\, Oluwole Ayodele\, Saurav Bisht\,\nToronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/312336
URL:https://www.ieeetoronto.ca/event/credit-card-fraud-detection-students-research-in-ml-and-dl-at-durham-college/
LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/312336
CATEGORIES:Magnetics,Women in Engineering
ORGANIZER;CN="Reza Dibaj":MAILTO:reza.dibaj@ieee.org
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220426T180000
DTEND;TZID=America/New_York:20220426T190000
DTSTAMP:20260416T082716
CREATED:20220425T202413Z
LAST-MODIFIED:20220426T234759Z
UID:10000521-1650996000-1650999600@www.ieeetoronto.ca
SUMMARY:Fake News Detection – Students Research in ML and DL at Durham College
DESCRIPTION:The term “fake news” was pretty much unknown and unpopular a few decades ago\, but it has emerged as a massive monster in the digital era of social media. Fake news is spreading like wildfire these days\, and people share it without confirming it. Often\, it is to promote or enforce specific views\, and it is carried out through political agendas. Fake news refers to news that may or may not be correct and is widely disseminated via social media and other internet platforms. \nIn this digital age\, it is not easy to tackle the spread of fake news\, where thousands of information-sharing sites via fake news or misinformation can be shared. It has become a greater issue as AI advances\, bringing with it artificial bots that may be used to create and propagate fake news. The problem is critical because many individuals believe anything they read on the internet\, and those who are inexperienced or new to digital technologies are vulnerable to being misled. Fraud is another issue that can arise as a result of spam or harmful emails and communications.\nFake news has grown in popularity and spread as a result of recent political events. Humans are inconsistent\, if not outright terrible detectors of fake news\, as evidenced by the pervasive effects of the widespread onset of fake news. As a result\, efforts have been made to automate detecting fake news. The most prominent of these attempts are “blacklists” of unreliable sources and authors. While these technologies are useful we need to account for more complex instances when trusted sources and authors leak fake news in order to provide a complete end-to-end solution. As a result\, the goal of this project was to develop a tool that used machine learning and natural language processing techniques to recognize the language patterns that distinguish fake and true news. The outcomes of this project show that machine learning can be effective in this situation. We developed a model that detects a variety of intuitive indicators of real and fake news and an application to aid in the visual representation of the classification decision. We aim to give users the ability to classify news as fake or real and verify the website legitimacy that published it. \nSpeaker(s): Roshna Babu\, Abraham Mathew\, Neha Joseph\nToronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/312334
URL:https://www.ieeetoronto.ca/event/fake-news-detection-students-research-in-ml-and-dl-at-durham-college/
LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/312334
CATEGORIES:Magnetics,Women in Engineering
ORGANIZER;CN="Reza Dibaj":MAILTO:reza.dibaj@ieee.org
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20211029T180000
DTEND;TZID=UTC:20211029T200000
DTSTAMP:20260416T082716
CREATED:20211001T152640Z
LAST-MODIFIED:20211128T135459Z
UID:10000471-1635530400-1635537600@www.ieeetoronto.ca
SUMMARY:Building your online presence by creating your personal website
DESCRIPTION:A personal website is essential in this world where an online presence is a must. Through this workshop\, Simon will show you how to buy your domain\, the cheapest and more efficient way to host it\, how to get SSL certificates for your website and the best practices to design and implement your website.  Speaker(s): Simon Bermudez\,   Virtual: https://events.vtools.ieee.org/m/284161
URL:https://www.ieeetoronto.ca/event/building-your-online-presence-by-creating-your-personal-website/
LOCATION:Virtual: https://events.vtools.ieee.org/m/284161
CATEGORIES:Magnetics,Women in Engineering
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20210726T120000
DTEND;TZID=UTC:20210726T130000
DTSTAMP:20260416T082716
CREATED:20210708T233315Z
LAST-MODIFIED:20220105T225837Z
UID:10000442-1627300800-1627304400@www.ieeetoronto.ca
SUMMARY:Sustainable Service Pricing in Cloud Ecosystems
DESCRIPTION:Energy efficiency\, which has emerged as a top priority in cloud ecosystems\, is the outcome of appropriate pricing mechanisms and resource allocations. Static pricing mechanisms are the most dominant approach among all the others. They are simple to implement for the service providers and easy to understand for the service users. Inaccurate price calculation and low efficient resource allocation in static pricing mechanisms made researchers discover other solutions to overcome these issues. Double auction mechanisms are among the most appropriate dynamic models. The main challenge of conventional double auction mechanisms is not considering the cloud ecosystems’ specifications\, such as dynamic online features. The term dynamic refers to the many variable parameters in cloud ecosystems\, and they constantly change. Conventional static offline pricing solutions are set based on a series of parameters before running the process. In dynamic online methods\, we customize our pricing models based on dynamic and current parameters. Also\, we continuously optimize these methods to attain optimal results. In this seminar\, firstly\, we define a Dynamic Online Double Auction Mechanism (DODAM) for the IaaS environment\, which covers a broader range of IaaS parameters by considering the dynamic online features of such markets. Considering the features of cloud dynamic online ecosystems\, DODAM provides an appropriate price scheduling for service providers and service users. Cloud secondary market is a new paradigm in IaaS ecosystems. In these markets\, brokers and reseller buyers have attained their resources from service providers of the cloud primary markets in the form of timed packages and repackage them into smaller chunks. As unsold packages do not transfer to the next intervals\, brokers and reseller buyers need to sell their packages as much as possible. We develop a mechanical design that includes a market-based pricing model and a resource allocation algorithm in such markets as our second contribution. Next\, by formulating the inherent competitive features in cloud secondary markets\, we improve the pricing and resource allocation mechanisms in such competitive ecosystems. In the last contribution\, we proposed a Priority-based Dynamic Online Double Auction Model (PB-DODAM)\, considering the perishability and time constraints of traded resources in IaaS secondary markets. The provided experimental results show that all proposed mechanisms drastically increase resource utilization and the overall utility. \nSpeaker(s): Dr. Reza Dibaj \nVirtual: https://events.vtools.ieee.org/m/276942
URL:https://www.ieeetoronto.ca/event/sustainable-service-pricing-in-cloud-ecosystems/
LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/276942
CATEGORIES:Magnetics,Women in Engineering
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20210719T120000
DTEND;TZID=UTC:20210719T130000
DTSTAMP:20260416T082716
CREATED:20210708T233314Z
LAST-MODIFIED:20220105T225731Z
UID:10000440-1626696000-1626699600@www.ieeetoronto.ca
SUMMARY:Distributed Machine Learning 101
DESCRIPTION:Machine Learning is an indispensable part of data science\, and there is no need to have a thorough programming background to benefit from it. Machine Learning (ML) and statistical techniques have provided a new era that enables us to convert the data into information and transform it into actionable knowledge. SciKit and TensorFlow are two states of the art libraries that can be used in Python\, and this seminar will open the gate to know their bases. The first seminar is about “Hello World!” Machine Learning program\, using the python language and SciKit learn library. \nSpeaker(s): Dr. Reza Dibaj \nVirtual: https://events.vtools.ieee.org/m/276938
URL:https://www.ieeetoronto.ca/event/distributed-machine-learning-101/
LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/276938
CATEGORIES:Magnetics,Women in Engineering
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20210223T133000
DTEND;TZID=America/Toronto:20210223T143000
DTSTAMP:20260416T082716
CREATED:20210430T023721Z
LAST-MODIFIED:20210501T002947Z
UID:10000354-1614087000-1614090600@www.ieeetoronto.ca
SUMMARY:Isola High Speed Materials and Copper Foil Selection
DESCRIPTION:On Tuesday\, February 23\, 2021 at 1:30 p.m.\, Michael J. Gay from Isola will present the technical presentation “Isola High Speed Materials and Copper Foil Selection“. \nDay & Time: Tuesday\, February 23\, 2021|\n1:30 p.m. – 2:30 p.m. \nSpeaker: Michael J. Gay \nOrganizer(s): IEEE KW EMC/MAG joint Chapter\, University of Toronto AP Student Chapter \nLocation: Virtual – WebEx \nContact: Ming Chang Wang\, Parinaz Naseri \nAbstract: \nAre you running 10Gbps+ signal channel in your system? \nWhat PCB materials are suitable for 10Gbps+ application? \nHow copper layer surface roughness affecting Signal Integrity\, RF\, etc? \nIEEE KW EMC/MAG joint Chapter and University of Toronto AP Student Chapter invite you to join this technical presentation of “Isola High Speed Materials and Copper Foil Selection” by Michael J. Gay from Isola. \nThis event will be recorded for Asia Region attendees. Please register even you are not able to join live\, so that you will be provided for a link with the recorded version later. \nAgenda: \n\nSI (Signal Integrity) Performance – Laminate versus SITV (Signal Integrity Test Vehicle) testing\nTech road map\nComparing Isola HSD product options\nCopper foil performance factors\nIsola Product Stack\nIsola foil testing method and results\n\nRegister: Please visit https://events.vtools.ieee.org/m/260528 to register. \nBiography: \nMichael J. Gay currently holds the position of Director\, High Performance Products with Isola. Michael has been with Isola for 20 years and has 25 years of experience in laminate and PCB manufacturing industries. He has held various positions at Isola which include Technical Sales Manager and Director Emerging Products Asia Pacific Region where his responsibilities ranged from new product introduction\, PCB process development and technical support and troubleshooting for Isola customers. Since returning from his role in Asia\, he has worked closely with major industry OEM’s to develop and qualify Isola materials for the next generation of technology. \nMichael is also active in various PCB industry organizations where he currently provides technical expertise to industry critical committees and projects. He received his Bachelor of Science in Mechanical Engineering and Masters of Business Administration from Portland State University.
URL:https://www.ieeetoronto.ca/event/isola-high-speed-materials-and-copper-foil-selection/
LOCATION:Kitchener\, Ontario Canada
CATEGORIES:Magnetics
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20200819T100000
DTEND;TZID=America/Toronto:20200819T110000
DTSTAMP:20260416T082716
CREATED:20210430T023543Z
LAST-MODIFIED:20210430T235353Z
UID:10000327-1597831200-1597834800@www.ieeetoronto.ca
SUMMARY:An Introduction to Django Web Development with Python
DESCRIPTION:On Wednesday\, August 19\, 2020 at 10:00 a.m.\, Suho Kang will present “An Introduction to Django Web Development with Python”. \nDay & Time: Wednesday\, August 19\, 2020\n10:00 a.m. – 11:00 a.m. \nSpeaker: Suho Kang \nOrganizer: IEEE Toronto WIE\, Magnetics Chapter \nLocation: Virtual – Zoom \nContact: Seyed M. Reza Dibaj\, Maryam Davoudpour \nAbstract: Django is a Python Web framework that encourages rapid development and clean design.\nSo many functionalities are already built in this framework by experienced developers\, so you do not have to re-invent the wheel\, and Django will take care of those hassles for you.\nIn our event\, we will be building a basic Django Web Application from scratch in a hands-on approach.\nAt the end of this course\, you will be familiar with how to make a virtual environment\, Django installation process\, an HTTP request handling\, and a CSS file and image file importing steps. \n(Requirements: The requirements are knowing the basic python\, HTML\, and CSS\, and the recommended platform consists of anaconda (preferred)\, Python3\, and the installed git bash on your system.) \nIt is highly recommended to participate in Getting Started with Python and Applied Data Science with pandas\, before attending this event. \nRegister: Please visit https://events.vtools.ieee.org/m/237004 for more information and to register.
URL:https://www.ieeetoronto.ca/event/an-introduction-to-django-web-development-with-python/
LOCATION:Toronto\, Ontario Canada
CATEGORIES:Magnetics,Women in Engineering
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20200818T100000
DTEND;TZID=America/Toronto:20200818T110000
DTSTAMP:20260416T082716
CREATED:20210430T023543Z
LAST-MODIFIED:20210430T235202Z
UID:10000326-1597744800-1597748400@www.ieeetoronto.ca
SUMMARY:Applied Data Science with pandas
DESCRIPTION:On Tuesday\, August 18\, 2020 at 10:00 a.m.\, Rafael Afonso Silva will present “Applied Data Science with pandas”. \nDate & Time: Tuesday\, August 18\, 2020\n10:00 a.m. – 11:00 a.m. \nSpeaker: Rafael Afonso Silva \nOrganizer: IEEE Toronto WIE\, Magnetics Chapter \nLocation: Virtual – Zoom \nContact: Seyed M. Reza Dibaj\, Maryam Davoudpour \nAbstract: Pandas is a fast\, powerful\, flexible and easy to use environment on top of the Python programming language. It is an open-source data analysis and manipulation tool\, which has made our life easier in the Data Science world. If you work or intend to work with data using Python\, you need to know pandas\, either for Data Analysis\, Data Science or Machine Learning. In our workshop\, we will provide a hands-on introduction to the pandas library and will learn how to use its amazing features to extract\, analyze and manipulate our data from different data sources. \n(Prerequisite: You need to have basic programming knowledge in Python) \nRegister: Please visit https://events.vtools.ieee.org/m/237002 for more information and to register.
URL:https://www.ieeetoronto.ca/event/applied-data-science-with-pandas/
LOCATION:Toronto\, Ontario Canada
CATEGORIES:Magnetics,Women in Engineering
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20200817T100000
DTEND;TZID=America/Toronto:20200817T110000
DTSTAMP:20260416T082716
CREATED:20210430T023542Z
LAST-MODIFIED:20210430T235045Z
UID:10000324-1597658400-1597662000@www.ieeetoronto.ca
SUMMARY:Getting Started with Python
DESCRIPTION:On Monday\, August 17\, 2020 at 10:00 a.m.\, Sathish Ravichandran will be presenting “Getting Started with Python”. \nDay & Time: Monday\, August 17\, 2020\n10:00 a.m. – 11:00 p.m. \nSpeaker: Sathish Ravichandran \nOrganizers: IEEE Toronto WIE\, Magnetics Chapter \nLocation: Virtual – Zoom \nContact: Seyed M. Reza Dibaj\, Maryam Davoudpour \nAbstract: Python is an easy to learn programming language with a wide variety of well-paying jobs in many fields\, including data science\, web development\, network programming and so on. \nThis workshop is aimed at complete beginners who have never programmed before\, as well as existing programmers who want to increase their career options by learning Python\, especially if you are pursuing a career in data science\, AI\, web development\, big data\, web testing\, or programming for smart devices in Python. \nRegister: Please visit https://events.vtools.ieee.org/m/237001 for more details and to register.
URL:https://www.ieeetoronto.ca/event/getting-started-with-python/
LOCATION:Tornoto\, Ontario Canada
CATEGORIES:Magnetics,Women in Engineering
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20191201T103000
DTEND;TZID=America/Toronto:20191201T123000
DTSTAMP:20260416T082716
CREATED:20210430T023531Z
LAST-MODIFIED:20210430T233316Z
UID:10000296-1575196200-1575203400@www.ieeetoronto.ca
SUMMARY:IEEE Toronto Centennial Workshop: Building An ASP.NET Core Application
DESCRIPTION:Sunday December 1st\, 2019 at 10:30 a.m. Thiago do Nascimento Fontes and Kelvin Trinh will be presenting “IEEE Toronto Centennial Workshop: Building An ASP.NET Core Application”. \nDay & Time: Sunday\, December 1st\, 2019\n10:30 a.m. – 12:30 p.m. \nSpeakers: Thiago do Nascimento Fontes\, Kelvin Trinh \nOrganizers: Magnetics Chapter\, IEEE Toronto Centennial College Chapter\, WIE IEEE Toronto \nLocation: Room A3-11\nCentennial College\, Progress Campus\n941 Progress Ave.\, Toronto\, Ontario\, M1G 3T8 \nContact: Reza Dibaj \nAbstract: ASP.NET Core is a cross-platform\, high-performance\, open-source framework for building modern\, cloud-based\, Internet-connected applications. A huge number of developers have used this technology to develop amazing websites. In our event\, we start from scratch to develop a mini-project using ASP.Net Core to show every step in a hands-on approach. We will build a simple\, yet realistic ASP.NET Core application and showcase the feature of Entity Framework Core.
URL:https://www.ieeetoronto.ca/event/ieee-toronto-centennial-workshop-building-an-asp-net-core-application/
LOCATION:Room A3-11 Centennial College\, Progress Campus 941 Progress Ave.\, Toronto\, Ontario\, M1G 3T8
CATEGORIES:Magnetics,Women in Engineering
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20190730T143000
DTEND;TZID=America/Toronto:20190730T153000
DTSTAMP:20260416T082716
CREATED:20210430T023526Z
LAST-MODIFIED:20210430T232047Z
UID:10000178-1564497000-1564500600@www.ieeetoronto.ca
SUMMARY:IEEE Toronto Centennial Workshop: Distributed Machine Learning\, The Second Step
DESCRIPTION:Tuesday July 30th\, 2019 at 2:30 p.m. Reza Dibaj\, Chair of Magnetics Chapter in the IEEE Toronto Section\, will be presenting “IEEE Toronto Centennial Workshop: Distributed Machine Learning\, The Second Step”. \nDay & Time: Tuesday July 30th\, 2019\n2:30 p.m. ‐ 3:30 p.m. \nSpeaker: Reza Dibaj\nChair of Magnetics Chapter\, IEEE Toronto Section \nOrganizers: Magnetics Chapter\, IEEE Toronto Centennial College Chapter\, WIE IEEE Toronto \nLocation: Room B3-09\nCentennial College\, Progress Campus\n941 Progress Ave.\, Toronto\, Ontario\, M1G 3T8 \nContact: Reza Dibaj \nAbstract: At the beginning of the workshop\, we quickly recap what we did in the previous session and knowing more about the definition of good features in our datasets. To continue our journey that we have started in the previous workshop\, we will dive deeper into ML by applying our Decision Tree algorithm on a classical iris dataset. We will thoroughly practice training and testing data\, using a step-by-step hands-on. Finally\, we will use visualization tools to show what is happening under the hood in a decision tree and how it works as one of the most interpretable algorithms in ML.
URL:https://www.ieeetoronto.ca/event/ieee-toronto-centennial-workshop-distributed-machine-learning-the-second-step/
LOCATION:Room B3-09 Centennial College\, Progress Campus 941 Progress Ave.\, Toronto\, Ontario\, M1G 3T8
CATEGORIES:Magnetics,Women in Engineering
END:VEVENT
END:VCALENDAR