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Machine Learning
2,545,518 Views · 4 years ago

Generative AI
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Gulshan Kumar & T-Series Presents A Sohail Khan Productions "Ready" Directed by Anees Bazmee starring Salman Khan and Asin in the lead roles. It also features Paresh Rawal, Arya Babbar, and Mahesh Manjrekar in supporting roles, while Ajay Devgn, Sanjay Dutt, Kangana Ranaut, Zarine Khan, and Arbaaz Khan in cameo appearances.

Movie Credits:
Movie Name: Ready
Actors: Salman Khan, Asin, Paresh Rawal, Arya Babbar, and Mahesh Manjrekar
Director: Anees Bazmee
Producer: Bhushan Kumar, Sohail Khan, Krishan Kumar
Music: Pritam, Devi Sri Prasad
Lyrics: Neelesh Misra, Amitabh Bhattacharya, Kumaar, Ashish Pandit
Music Label: T-Series
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Generative AI
2,544,649 Views · 4 years ago

How is a beginner supposed to get started learning machine learning? I'm going to describe a free 3 month curriculum to help you go from beginner to well-versed in modern machine learning. Transformers, Diffusers, Large Language Models, and dozens of new ML Ops tools have been released the past few years! The field of ML has changed so much and there are so many new tools to learn. Using the help of AI services, we can learn a lot faster than usual. This learning plan is something I'd create for myself if I were to get started today, but I'm going to open source it for you guys. This curriculum will cover all the math concepts, machine learning, deep learning, ML Ops, and tons of cool projects to get you up to speed with the field as fast as possible. If anyone asks how to best get started with machine learning, direct them to this video!

Curriculum from this video:
https://github.com/llSourcell/LearnML

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Curriculum Links
-----------------------------------------------------
Month 1: Machine Learning

Week 1: Python Fundamentals - https://allendowney.github.io/DSIRP/index.html

Week 2: Math of Machine Learning -
http://www.xaktly.com/XMathMain.html

Week 3: Data Analysis -
https://www.kaggle.com/learn

Week 4: Machine Learning Techniques -
https://github.com/ipython-books/cookbook-2nd

Month 2: Deep Learning

Week 1: Neural Networks
http://d2l.ai/

Week 2: Transformers
https://huggingface.co/course/chapter1/1

Week 3: Diffusers
https://www.fast.ai/posts/part2-2022-preview.html

Week 4: Deep Reinforcement Learning
https://simoninithomas.github.io/deep-rl-course/

Month 3: Machine Learning Operations

Week 1: Design -
https://madewithml.com/

Week 2: Development -
https://fullstackdeeplearning.com/course/2022/

Week 3: Production -
https://github.com/DataTalksClub/mlops-zoomcamp

Week 4: Data Engineering -
https://github.com/DataTalksCl....ub/data-engineering-




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