Study plan

Current Studies

Andrey Karpathy Neural Networks: Zero to Hero Playlist

Course Link

• The spelled-out intro to neural networks and backpropagation: building micrograd. Notes
• The spelled-out intro to language modeling: building makemore
• Building makemore Part 2: MLP
• Building makemore Part 3: Activations & Gradients, BatchNorm
• Building makemore Part 4: Becoming a Backprop Ninja
• Building makemore Part 5: Building a WaveNet
• Let’s build GPT: from scratch, in code, spelled out.
• Let’s build the GPT Tokenizer
• Let’s reproduce GPT-2 (124M)

Course.fast.ai. Practical Deep Learning

Course Link
Part 1

• 1: Getting started
• 2: Deployment
• 3: Neural net foundations
• 4: Natural Language (NLP)
• 5: From-scratch model
• 6: Random forests
• 7: Collaborative filtering
• 8: Convolutions (CNNs)
• Bonus: Data ethics

Part 2

• 9: Stable Diffusion
• 10: Diving Deeper
• 11: Matrix multiplication
• 12: Mean shift clustering
• 13: Backpropagation & MLP
• 14: Backpropagation
• 15: Autoencoders
• 16: The Learner framework
• 17: Initialization/normalization
• 18: Accelerated SGD & ResNets
• 19: DDPM and Dropout
• 20: Mixed Precision
• 21: DDIM
• 22: Karras et al (2022)
• 23: Super-resolution
• 24: Attention & transformers
• 25: Latent diffusion
• Bonus: Lesson 9a
• Bonus: Lesson 9b

Past Completed Studies

Learn PyTorch for deep learning in a day. Literally.

Course Link

• First hour
• Second hour
• Third hour
• Fourth hour
• Chapter 0. PyTorch Fundamentals. Notebook
• Fifth hour
• Sixth hour
• Seventh hour
• Eighth hour
• Chapter 1. PyTorch Workflow. Notebook
• Ninth hour
• Tenth hour
• Eleventh hour
• Twelfth hour
• Thirteenth hour
• Fourteenth hour
• Chapter 2. PyTorch Classification. Notebook
• Fifteenth hour
• Sixteenth hour
• Seventeenth hour
• Eighteenth hour
• Nineteenth hour
• Chapter 3. PyTorch Computer Vision. Notebook
• Twentieth hour
• Twenty-first hour
• Twenty-second hour
• Twenty-third hour
• Twenty-fourth hour

Nest js

• NestJs - Zero to Hero

Learn PyTorch for deep learning in a day. Literally.

Course Link

• First hour
• Second hour
• Third hour
• Fourth hour
• Chapter 0. PyTorch Fundamentals. Notebook
• Fifth hour
• Sixth hour
• Seventh hour
• Eighth hour
• Chapter 1. PyTorch Workflow. Notebook
• Ninth hour
• Tenth hour
• Eleventh hour
• Twelfth hour
• Thirteenth hour
• Fourteenth hour
• Chapter 2. PyTorch Classification. Notebook
• Fifteenth hour
• Sixteenth hour
• Seventeenth hour
• Eighteenth hour
• Nineteenth hour
• Chapter 3. PyTorch Computer Vision. Notebook
• Twentieth hour
• Twenty-first hour
• Twenty-second hour
• Twenty-third hour

Kaggle

• Geospatial Analysis
• Data Cleaning
• Machine Learning Explainability
• Time Series
• Advanced SQL
• Feature Engineering
• Data Visualization
• Pandas
• Intro to AI Ethics
• Python
• Computer Vision
• Intro to SQL
• Intro to Game AI and Reinforcement Learning
• Kaggle - Intermediate Machine Learning
• Kaggle - Intro to Deep Learning
• Kaggle - Intro to Programming
• Intro to Machine Learning

MIPT (Moscow Institute of Physics and Technology)

• Mathematics and Python for Data Analysis
• Supervised Learning
• Finding Structure in Data