"The book is an exceptionally well-written technical Python book for beginners that uses active learning techniques. If you're a beginner to intermediate-level coder, this book will significantly improve your Python skills. It's easy to read, and solving the problems is fun and satisfying." Dr. Daniel Zingaro is an award-winning Associate Professor of Computer Science in the teaching stream at University of Toronto Mississauga, and is internationally recognized for his expertise in Active Learning. He is also the author of Algorithmic Thinking (No Starch Press, 2021).
History: For my masters research project at University of Toronto, I was given airport Xray baggage scan images containing gun and knife to develop a model that performs an automatic detection of gun and knife in the baggage. Given only a small amount of Xray images, I am using Domain Adaptation by using a large number of normal non-Xray images of gun and knife from the web to train a model and adapting the model to perform well on the Xray images. In this post, I will address a strange behaviour of ResNet50 and show how the t-SNE visualization technique helped clear up the fog. In Chapter 3.2, I addressed a concerning and unintuitive behaviour of ResNet50 that was fine-tuned for gun vs. knife binary classification task using only web images (no Xray images). It classified images unrelated to gun or knife (e.g.
With the growing demand for AI, many colleges or institutions have begun offering AI courses in Toronto, Canada, at various levels. The value of Artificial Intelligence has skyrocketed over the past few years. That is why Artificial Intelligence courses are in the early stages. Many early colleges have shown lessons in their curriculum by recognizing its growing popularity and demand. And not just science colleges or technical colleges but, other educational institutions are doing the same.
Become a complete Python developer! Join a live online community of over 330,000 developers and a course taught by an industry expert that has actually worked both in Silicon Valley and Toronto. This is a brand new Python course just launched for 2020 (updated this month)! Graduates of Andrei's courses are now working at Google, Tesla, Amazon, Apple, IBM, JP Morgan, Facebook, other top tech companies. Learn Python from scratch, get hired, and have fun along the way with the most modern, up-to-date Python course on Udemy (we use the latest version of Python).
FreshBooks has a big vision. We launched in 2003 but we're just getting started and there's a lot left to do. We're a high performing team working towards a common goal: building an elite online accounting application to help small businesses better handle their finances. Known for extraordinary customer service and based in Toronto, Canada, FreshBooks serves paying customers in over 120 countries. FreshBooks is seeking a Data Engineer to join our team.
On August 8th, 2021, a team of four graduate students from the University of Toronto presented their ethical design in the world's first ever roboethics competition, the RO-MAN 2021 Roboethics to Design & Development Competition. During the competition, design teams tackled a challenging yet relatable scenario--introducing a robot helper to the household. The students' solution, entitled "Jeeves, the Ethically Designed Interface (JEDI)", demonstrated how home robots can act safely and according to social and cultural norms. Click here to watch their video submission. JEEVES acted as an extension of the mother and the interface rules accommodated her priorities.
The ability of computers to understand and generate language took a huge leap forward in 2017 when researchers at Google developed new natural -anguage AI models called Transformers. Some of the experts who built and trained those seminal models have since branched out on their own by founding the Toronto-based startup Cohere, which today announced a new $40 million Series A funding round. The technology that undergirds Cohere's natural-language processing models was originally developed by the Toronto-based Google Brain team. Two of that team's members, Aidan Gomez and Nick Frosst (along with a third cofounder, Ivan Zhang), started Cohere two years ago to further develop and commercialize the models, which are delivered to customers through an API. Cohere is backed by neural network pioneer and Turing Award winner Geoffrey Hinton, who led the Toronto Google Brain team, as well as some other big names in the AI world like Stanford computer science professor Fei-Fei Li. "Very large language models are now giving computers a much better understanding of human communication," Hinton said in a statement to Fast Company.
At Toronto Womxn in Data Science our vision is to inspire and empower 1 million data-literate womxn, increase the recruitment and retention of womxn in data professions and encourage innovation in this space. Our enterprise strategy to enable our vision is to provide programming that celebrates womxn in data and educates those interested in the field through events, mentorship, and data product co-creation. Please fill out the following form to express your interest in being an expert at Toronto Womxn in Data Science's programming! Over the last 4 years, we've showcased the knowledge and career journeys of Womxn in Data Science across academia, industry, start-ups, and government. Our content has always been diverse, allowing us to keep our audience engaged and learning. Our themes cover technical, business, and ethics topics in data science. Some opportunities include: Annual Conference, Podcast feature, Data Media Club, Datathon Masterclass Instructor, Panelist, Inclusive Fellowship Program in house expert Annual Conference: The 5th Annual Womxn in Data Science Conference is from Wednesday, April 27th to Thursday, April 28th, 2022. We welcome you to submit a proposal to speak. Presentations will be a maximum of 30 minutes plus 5 minutes of Q&A. Facilitating a hands on workshop is also an acceptable format (max 2 hours in length. Podcast Feature: We have a podcast called Data Drop. Data Drop is a podcast meant to inform youth about the amazing learning and career opportunities in the field of Data Science. The segments are 15 minutes or less and available wherever you listen to your podcasts. Data Media Club: The Data Media Club is a chance for our community to increase their data literacy through film, books and art. Built to be completely virtual, we welcome attendees from coast to coast to join us. As a speaker at a data media club engagement, we're looking for hosts to drive meaningful conversations with authors, directors, or other media leaders who centre their work on data. Datathon Masterclass Instructors: Our 1st Datathon will be in January 2022. We're looking for experts in Product, Inclusive Design, Ethics, and Data Science to run a 30-45 minute masterclass on how the participants can tackle the design challenge. Panelist: We have microevents that run from 6-8pm EST. Upcoming Microevents are on November 17th on Natural Language Processing and January 19th on Data Engineering. The panel will run for an hour from 7-8pm. Inclusive Fellowship Program in house experts: We want to encourage women to not only pursue data careers but have a chance to position themselves as creators and not just consumers of data products. The program will place fellows on projects to use data science to create products and services that positively impact all women. The fellows will have a chance to use their work on the projects as portfolio-building content to help secure further employment post-fellowship. Our in house experts will help guide the fellows through the program. The program is set to launch in April 2022.
Created by Andrei Neagoie, Daniel BourkePreview this Course - GET COUPON CODE This is a brand new Machine Learning and Data Science course just launched and updated this month with the latest trends and skills for 2021! Become a complete Data Scientist and Machine Learning engineer! Join a live online community of 400,000 engineers and a course taught by industry experts that have actually worked for large companies in places like Silicon Valley and Toronto. Graduates of Andrei's courses are now working at Google, Tesla, Amazon, Apple, IBM, JP Morgan, Facebook, other top tech companies. You will go from zero to mastery! Learn Data Science and Machine Learning from scratch, get hired, and have fun along the way with the most modern, up-to-date Data Science course on Udemy (we use the latest version of Python, Tensorflow 2.0 and other libraries).