This video is the one of the most awaited video on our channel. It consists of a complete path or guidance of how/what/when/where to study the stuff for a Coding Stream Student in order to have good hands on Machine Learning.
It consists of a complete and Ideal strategy that a student should follow in order to get the most.
Be Positive, Be Strong…
Resources:
MIT OpencourseWare Linear Algebra: https://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-spring-2010/
3Blue1Brown Linear Algebra: https://www.youtube.com/watch?v=fNk_zzaMoSs&list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab
Rachel Thomas Linear Algebra: https://www.youtube.com/watch?v=8iGzBMboA0I&list=PLtmWHNX-gukIc92m1K0P6bIOnZb-mg0hY
3Blue1Brown Calculus: https://www.youtube.com/watch?v=WUvTyaaNkzM&list=PLZHQObOWTQDMsr9K-rj53DwVRMYO3t5Yr
Intro to Probability: https://www.edx.org/course/probability-the-science-of-uncertainty-and-data
Github Roadmap Link: https://github.com/mrdbourke/machine-learning-roadmap
Python GFG: https://www.geeksforgeeks.org/python-programming-language/
Element of AI: https://www.elementsofai.com/
Google ML Crash Course: https://developers.google.com/machine-learning/crash-course
MadewithML : https://madewithml.com/
workera : https://workera.ai/
kaggle : https://www.kaggle.com/competitions
DeepLearning Curriculum: https://www.deeplearning.ai/
Fastai Part1: https://course.fast.ai/
Fastai Part2: https://course19.fast.ai/part2
cs50 course: https://cs50.harvard.edu/ai/2020/
full stack DL: https://fullstackdeeplearning.com/march2019
useful Links:
– https://arxiv.org/
– https://madewithml.com/
– https://paperswithcode.com/
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