Neural Network Programming - Deep Learning with PyTorch
Learn to build and train neural networks using PyTorch, covering tensor operations, CNN architecture, data preparation, training loops, and performance optimization techniques for deep learning projects.
Intro to PyTorch Tutorial - Building Fashion Recognizer
Learn to build a fashion recognizer using PyTorch in this hands-on tutorial. Covers core functionality, network architecture, loss functions, optimizers, and TensorBoard integration for effective model training.
Inside TensorFlow - Summaries and TensorBoard
Explore TensorBoard and tf.summary API for data visualization in TensorFlow. Learn about API changes, log directories, event files, and best practices from a TensorFlow engineer.
How to Use Machine Learning AI in Unity - ML-Agents
Unlock the power of Machine Learning AI in Unity with ML-Agents. Learn installation, agent creation, training, and visualization to enhance your game development skills.
Complete TensorBoard Guide
Comprehensive guide to TensorBoard features including loss plots, image visualization, confusion matrices, hyperparameter tuning, embedding projections, and TensorFlow profiler for model optimization and analysis.
Pytorch TensorBoard Tutorial
Comprehensive guide to TensorBoard in PyTorch: plotting functions, hyperparameter search, image and weight visualization, and embedding projector. Practical examples included.
Long Short-Term Memory with PyTorch + Lightning
Learn to implement and train LSTM networks using PyTorch and Lightning, covering custom LSTM coding, PyTorch's built-in LSTM, and advanced training techniques for deep learning projects.
Batch Normalization in PyTorch - Adding Normalization to Convolutional Neural Network Layers
Learn to implement batch normalization in convolutional neural networks using PyTorch. Explore the benefits, create and compare networks, and optimize performance through hands-on coding and practical examples.
Fine-Tuning LLM with QLoRA on Single GPU - Training Falcon-7b on ChatBot Support FAQ Dataset
Learn to fine-tune Falcon-7b LLM on a custom dataset using QLoRA. Covers model loading, LoRA adapter implementation, fine-tuning, progress monitoring, and performance evaluation on chatbot support FAQs.
Fine-Tuning Alpaca- Train Alpaca LoRa for Sentiment Analysis on a Custom Dataset
Learn to fine-tune Llama 7B with Alpaca LoRa on a custom bitcoin sentiment dataset. Covers data preprocessing, model training, and performance analysis for sentiment detection in cryptocurrency tweets.
Machine Learning Using Kubeflow and Kubernetes
Explore machine learning workflows on Kubernetes using Kubeflow, covering deployment, training, inference, and advanced features like hyperparameter tuning and automated pipelines.
Inside TensorFlow - TF Debugging
Explore TensorFlow debugging techniques for TF 2 and TF 1, covering tensor value printing, device placement, graph visualization, and step debugging in Keras models.