Trillion Parameter Models Are Here
Explore ZeRO-Infinity's breakthrough in training trillion-parameter ML models with limited GPUs, revolutionizing large-scale deep learning and expanding possibilities for AI researchers and practitioners.
Building Makemore - MLP
Implement a multilayer perceptron character-level language model, covering machine learning basics like model training, hyperparameter tuning, evaluation, and addressing under/overfitting.
The Spelled-Out Intro to Language Modeling - Building Makemore
Comprehensive tutorial on building a bigram character-level language model, covering tensor operations, neural networks, and PyTorch fundamentals for natural language processing tasks.
AI Body Language Decoder with MediaPipe and Python
Learn to decode body language using MediaPipe and Python. Build custom pose classification models to interpret facial and body landmarks in real-time with OpenCV, Pandas, and Scikit-Learn.
Forecasting Weather with Neural Prophet and Python
Learn to forecast weather using Neural Prophet and Python. Preprocess data, train models, and generate accurate temperature predictions with this hands-on tutorial.
Build a Deep Iris Detection Model Using Python and Tensorflow - Keypoint Detection
Develop an iris tracking model using keypoint detection with TensorFlow and Python. Learn data preparation, model creation, training, and real-time detection for advanced computer vision applications.
Build a Deep Audio Classifier with Python and Tensorflow
Learn to build a deep audio classifier using Python and TensorFlow, covering data loading, preprocessing, model creation, and prediction for audio classification tasks.
Build Your First Model with PyTorch and Python - PyTorch Tutorial for Beginners
Learn to implement a Simple Linear Regression model using PyTorch, covering data exploration, model creation, tensor conversion, training, and prediction analysis in this beginner-friendly tutorial.
Building a GAN From Scratch With PyTorch - Theory + Implementation
Learn to build a Generative Adversarial Network from scratch using PyTorch and PyTorch Lightning, covering theory, implementation, and testing in this comprehensive tutorial.
Neural Nets for NLP - Structured Prediction Basics
Explore structured prediction in NLP, covering perceptron algorithms, max-margin objectives, and exposure bias remedies. Learn techniques for modeling output interactions and training globally normalized models.
Neural Nets for NLP - Class Introduction & Why Neural Nets?
Introduction to neural networks for NLP, covering tasks, challenges, and potential solutions. Explores basic concepts, algorithms, and implementations using examples like sentence classification and continuous bag of words models.
TorchStudio - Deep Learning Toolkit
Hands-on guide to TorchStudio: Access PyTorch datasets, train models, and compare results. Ideal for beginners and experienced users in the PyTorch ecosystem.
Diffusion Models - Google Colab Experimentation with Code and Prebuilt Models - Part 2
Hands-on exploration of Diffusion Models using Google Colab, covering probabilistic implementations and prebuilt models. Includes code examples and practical demonstrations of the denoising process.
Deep Understanding of MNIST Problem and Its CNN Solution Using CNN Explainer
Comprehensive tutorial on MNIST problem and CNN solution using CNN Explainer. Covers dataset preparation, model architecture, training, and evaluation. Ideal for beginners in deep learning and neural networks.
A Visual Introduction to Modern and Scalable Machine Learning Pipeline
Visual guide to modern, scalable machine learning pipelines: from data prep to deployment. Covers key stages like training, validation, inference, feature stores, and model registry. Ideal for understanding ML infrastructure evolution.
Phi 1.5 - The Small Model Getting Big Results
Explore Phi 1.5, a small yet powerful language model. Learn about its development, capabilities, and potential applications through in-depth analysis and hands-on coding examples.
Creating an Animal Segmentation Model with U-Net and TensorFlow Keras
Learn to implement and train a U-Net model for animal segmentation using TensorFlow/Keras. Covers data preprocessing, model architecture, training, and evaluation with practical code examples.
Deep Learning and Energy Models for Fine Dead Wood Segmentation - Jacquelyn Shelton
Explore deep learning and energy models for fine dead wood segmentation in climate research, focusing on carbon cycle implications and advanced image analysis techniques.
Reinforcement Learning for Gaming - Full Python Course
Comprehensive guide to applying reinforcement learning in gaming using Python and Stable Baselines 3, covering Mario, Doom, Street Fighter, and Chrome Dino with practical missions and best practices.
Tune and Evaluate a Decision Tree Model with Scooby Doo Episodes
Learn to predict Scooby Doo monster status using decision trees. Explore model tuning, visualization, and simplification techniques with Julia Silge's practical demonstration.
Subword Features in Machine Learning for Text
Explore machine learning techniques for text analysis using tidymodels to predict Hawaii post offices from their names, with practical code examples and performance evaluation.