One of the best things about Deep Learning and A.I is the presence of state of the art open resources to learn it. So let's dive into the resources that you can use to learn Deep Learning and A.I.
Motivation to start :-
The Imitation Game:-One of the most influential papers and the origin of Turing test for A.I which A.I haven't passed even till now originated from this paper named “COMPUTING MACHINERY AND INTELLIGENCE” written by Alan Turing. It will ignite curiosity in the field.
Link for the paper :- https://redirect.cs.umbc.edu/courses/471/papers/turing.pdf
Building necessary prerequisites for Advanced concepts:-
1.Mathematics for AI:-AI is an interdisciplinary field and people from many domains and industries implement it with diverse educational backgrounds. But to dive deep into the domain requires a certain level of mathematics knowledge on concepts like high school level, Linear Algebra, Calculus,Probability and Statistics.To build the necessary mathematical prerequisites the following course is sufficient.Those who have prior knowledge on these topics can skip this course.
Blue1 Brown's Linear Essence of Algebra Series+Calculus Series+ Neural Network + Differential Equation Series:- I guess you must have already heard about this because of its fame and for good reasons only.One of the best educationist and mathematician of of current time Grant Sanderson have bring his creativity and mathematics together and build videos with great animations that are so amusing to watch for anyone.
1.Essence of linear algebra - YouTube, 2.The essence of calculus , 3.Neural networks - YouTube, 4.Differential equations - YouTube
2.Programming Knowledge:-You need to have a basic coding knowledge. You need not be a great coder but knowledge of at least one programming language is necessary. Python is the most famous language with many libraries and framework for AI. MIT had an open source course to introduce computational thinking with python.
Link:- MIT 6.0001 Introduction to Computer Science and Programming in Python, Fall 2016 - YouTube
Another good option to consider is:- CS50 by Harvard. Link:- CS50's Introduction to Programming with Python (CS50P) 2022 - YouTube
3.Machine learning Specialization:- The founder of Coursera and professor in Stanford University Andrew Ng has created this specialization which is super intuitive to grasp and begin with. You can learn it from Coursera by auditing the individual courses.Andrew Ng is one of the most influential researchers in Deep Learning in current time.
Link:- https://www.coursera.org/specializations/machine-learning-introduction
Kickstarting into Deep Learning:-
Fast.ai’s Online Courses:- Jeremy Howard who is instructor of this course and founder of fast.ai .As the name suggests you can dive into Deep Learning without getting too much depth of mathematics in a pragmatic way.
Link:-Practical Deep Learning for Coders
CS231n: Deep Learning for Computer Vision:-This course is a specialization in Computer Vision and a basic introduction in other neural networks offered by Stanford.Yo can get assignment and other course related materials on its official website:-
Link:-CS231n
Full Stack Deep Learning:- This course is made in a fashion that enables the learner from building the model to actually deploying in production. It made justice with its name and has a completeness of content. You need not do it end to end and only relevant parts can be choosen.
Link:- Course 2021 - Full Stack Deep Learning
Diving Deep into the Deep Learning:-The following resources are not introductory on knowledge but once you get familiar with the basics, you can follow these:
Books:- Though books are not very necessary if you have gone through these courses but if you are in academics and like to learn by books here is a good suggestion:-
Deep Learning by Ian Goodfellow:- Ian Goodfellow who invented GAN(Generative Adversarial Networks) is the author of this book. The book is academic in nature and has rigorous mathematics involved.
A HTML free version of book is:-Deep Learning
Research Papers:- To stay tuned with latest advancements in the field research papers are necessary to read. One of the best online free resources for that is paperswithcode.com .It is a website where you can find the latest research papers with their code implementations. Isn’t it cool?
Link:-Papers With Code
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