Here is the list of resources to learn Data Structures and Algorithms from beginner to advance:

📑 Prerequisite - MIT's Mathematics for Computer Science:
🔸 https://lnkd.in/ejdPkSs

📌 Khan Academy - Intro to algorithms:
🔸 https://lnkd.in/e8ZUWwz

📌 Introduction to Algorithms Book by Charles E. Leiserson, Clifford Stein, Ronald Rivest, and Thomas H. Cormen:
🔸 https://lnkd.in/e8iqvwn

📌 GeeksforGeeks - Data Structures Tutorials:
🔸https://lnkd.in/eiFACVV

📌 MIT - Introduction to Algorithms:
🔸 https://lnkd.in/eKavb3T

📌 Coursera - Data Structures and Algorithms Specialization:
🔸 https://lnkd.in/eDk8ZuY

📌 Coursera - Algorithms Specialization:
🔸 https://lnkd.in/ejJw5TV

📌 MIT - Advanced Data Structures:
🔸 https://lnkd.in/eKA7FD2

📌 GeeksforGeeks - Advanced Data Structures Tutorials:
🔸 https://lnkd.in/eu2J-Bm

💡 I also found this interesting website which explains Data Structures and Algorithms through animations -

🔸 https://visualgo.net/en


#منابع
#datastructures #algorithms #mathematics #machinelearning #computerscience

✴️ @AI_Python_EN
❇️ @AI_Python

The Math of Machine Learning - Berkeley University Textbook

The mathematical skills you need for starting your journey into the field of Machine Learning
Note: It should be noted that It doesn't cover all the mathematical skills you need for doing ML during your life, It's just a brief textbook which could help you to start learning more complicated mathematical concepts in ML

https://www.datasciencecentral.com/profiles/blogs/tutorial-the-math-of-machine-learning-berkeley-university
#mahine_learning #mathematics

MIT Technology Review:
A #NeuralNet solves the three-body problem 100 million times faster

#MachineLearning #mathematics

🔰 NeuralNet

🔰 Paper

❇️ @AI_Python_EN

"The International Mathematical Olympiad Grand Challenge"

The challenge: build an AI that can win a gold medal in the competition -- https://imo-grand-challenge.github.io

#ArtificialIntelligence #DeepLearning #Mathematics

I gladly announce my first online course on #Statistics and #Mathematics for #MachineLearning and #DeepLearning.

The course will be in English, QA sessions with instructor will be in Turkish, Azerbaijani , or English. TA sessions will be in English.

This is the first course of tribology courses to help attendees to capture foundations and mathematics behind ML,DL models.

The courses are listed as follow:
1. Statistics Foundation for ML
2. Introduction to Statistical Learning for ML
3. Advanced Statistical Learning for DL

The course starts on 15 Jan 2022, at 13:00 to 15:00 (Istanbul time):

Course Fee:
Free for unemployed attendees. :)
200 USD for employed candidates :).

Course contents:
https://lnkd.in/dcXKxUjE

Course Registration:
https://lnkd.in/dMpzMfMG

Please kindly share with the ones who are interested.

Here is the list of resources to learn Data Structures and Algorithms from beginner to advance:

📑 Prerequisite - MIT's Mathematics for Computer Science:
🔸 https://lnkd.in/ejdPkSs

📌 Khan Academy - Intro to algorithms:
🔸 https://lnkd.in/e8ZUWwz

📌 Introduction to Algorithms Book by Charles E. Leiserson, Clifford Stein, Ronald Rivest, and Thomas H. Cormen:
🔸 https://lnkd.in/e8iqvwn

📌 GeeksforGeeks - Data Structures Tutorials:
🔸https://lnkd.in/eiFACVV

📌 MIT - Introduction to Algorithms:
🔸 https://lnkd.in/eKavb3T

📌 Coursera - Data Structures and Algorithms Specialization:
🔸 https://lnkd.in/eDk8ZuY

📌 Coursera - Algorithms Specialization:
🔸 https://lnkd.in/ejJw5TV

📌 MIT - Advanced Data Structures:
🔸 https://lnkd.in/eKA7FD2

📌 GeeksforGeeks - Advanced Data Structures Tutorials:
🔸 https://lnkd.in/eu2J-Bm

💡 I also found this interesting website which explains Data Structures and Algorithms through animations -

🔸 https://visualgo.net/en


#منابع
#datastructures #algorithms #mathematics #machinelearning #computerscience

✴️ @AI_Python_EN
❇️ @AI_Python

📚 Mathematics for Machine Learning | University of California, Berkeley
کتاب آموزش ریاضیات برای یادگیری ماشین. خلاصه بودن کتاب می‌تونه توی روند آموزش مفید باشه.

👤 Garrett Thomas

🔗 http://gwthomas.github.io/docs/math4ml.pdf

#Machine_Learning #Mathematics
#Books

@ai_python

📌 Short Notes On Ai: Chris Albon
کریس‌البون؛ مدیر بخش یادگیری‌ماشین ویکی‌مدیا یک سایت داره که آموزش‌ها و مقالات مختلفی در زمینه پایتون، یادگیری‌ماشین و عملیات ماشین‌لرنینگ منتشر کرده. سر زدن بهش می‌تونه براتون مفید باشه.

🔗 https://chrisalbon.com/Home

#MachineLearning #NeuralNetworks
#LLMs #Python #OOP #MLOps
#Mathematics #DataScience

@ai_python

📚 Mathematics and probability for machine learning
تقریبا تمام تکنیک‌های علم داده و روش‌های یادگیری ماشین دارای برخی جنبه‌های عمیق ریاضیاتی هستن. در نتیجه برای درک بیشتر اونها بهتره یه تسلط نسبی به مباحث ریاضی داشته باشید. اینجا ۳ تا کتاب خوب برای ریاضیات و احتمال قرار دادم که می‌تونید استفاده کنید.

🔗 Mathematics for Machine Learning
🔗 Intro to Probability for Data Science
🔗 Mathematics for Machine Learning

#Mathematics #MachineLearning
#Probability #DataScience

@ai_python

📽 Mathematics for Ai | Persian Course
آموزش ریاضیات برای هوش‌مصنوعی و یادگیری ماشین به زبان فارسی

🔗 https://www.youtube.com/playlist?list=PLe_DUrcBPdbIRye6Dw_UdhR8a7Zqvb_BA

#Mathematics #Math
#Ai #MachineLearning

@ai_python