If you have some background in machine learning and you'd like to learn how to quickly improve the quality of your models, you're in the right place! In this course, you will accelerate your Machine Learning expertise by learning how to:
Along the way, you'll apply your knowledge by completing a hands-on exercise with real-world data for each new topic. The hands-on exercises use data from the Housing Prices Competition for Kaggle Learn Users, where you'll use 79 different explanatory variables (such as the type of roof, number of bedrooms, and number of bathrooms) to predict home prices. You'll measure your progress by submitting predictions to this competition and watching your position rise on the leaderboard!
For more details, you can check it out below 👇
https://www.kaggle.com/learn/intermediate-machine-learning
Prerequisites:
1. Have access to a Browser (preferably Google Chrome)
2. Sign up to Kaggle
3. Eager to Learn !!!
4.Have Completed "Intro to Machine Learning" course
Chubb
AI Developer
Vyas is a Data Scientist by day and writer/mentor by night. His work revolves around dealing with text data which is actually called Natural Language Processing. He finished my Masters at the University of Waterloo in the Electrical and Computer Engineering department.
Apart from his professional life, he also volunteers at the Waterloo student newspaper called Imprint to write articles…
Vyas is a Data Scientist by day and writer/mentor by night. His work revolves around dealing with text data which is actually called Natural Language Processing. He finished my Masters at the University of Waterloo in the Electrical and Computer Engineering department.
Apart from his professional life, he also volunteers at the Waterloo student newspaper called Imprint to write articles(links inside LinkedIn) about various topics and occasionally he plays the guitar.
University of Alberta
MSc Student
Tales is an MSc in Computing Science student at the University of Alberta. He currently works with Neural Program Synthesis with Professor Levi Lelis, bringing neural representation learning to guide the search of programmatic policies. He sees the set of tools that Machine Learning offers as a leading way to reason and solve many tasks that are relevant to society. His objective as a Machine Learning enthusiast is to make an impact in such a way, developing tools that can benefit those who are in need. In the past, he has worked with using computer vision in medical applications and with deploying and evaluating Internet of Things sensor networks. He is also a big game enthusiast: video games, board games or card games, just name it and he will be interested!
Canadian Centre for Mapping and Earth Observation
GDG Organizer
Treasurer
Event & Technical
Softmax Data
Event & Technical
GDG Cloud Edmonton
Marketing
Volunteer
GDG Co-organizer
Volunteer
