Using Semantic Search to Find GIFs
Learn to build a GIF search engine using semantic search, exploring data preparation, vector databases, and querying techniques for more accurate and context-aware results.
TensorFlow Tutorial 2022
Comprehensive TensorFlow tutorial covering tensors, data handling, neural networks, and model building. Learn to create, compile, and evaluate machine learning models using practical examples.
Chat in LangChain
Explore LangChain's chat features, including ChatOpenAI object, message types, and prompt templates. Learn to leverage these tools for enhanced AI interactions and natural language processing applications.
ChatGPT API in Python
Learn to integrate and utilize the ChatGPT API in Python, from basic queries to building a Gradio chat application, with practical examples and code demonstrations.
Implementing a Neural Network From Scratch in Python
Step-by-step implementation of a neural network using Python and numpy, focusing on data representation and forward propagation for a Multilayer Perceptron.
ChatGPT API in Python - How to Build a Custom AI Chat App
Learn to build a custom AI chat app using ChatGPT API in Python. Create a terminal client, store chat history, modify AI personality, and explore practical applications like a real estate AI assistant.
The Hamiltonian Monte Carlo Revolution Is Open Source - Probabilistic Programming with PyMC3
Explore Bayesian statistical computation and Hamiltonian Monte Carlo algorithms using PyMC3, an open-source probabilistic programming package. Learn to apply these advanced techniques to complex models in Python.
Machine Learning for Continuous Integration - Andrea Frittoli & Kyra Wulffert - ODSC Europe 2019
Explore machine learning techniques for analyzing CI/CD pipeline data, extracting insights, and automating failure identification using open-source tools like TensorFlow and Pandas with real-life OpenStack community data.
Introduction to Neural Networks in Python - Tensorflow-Keras
Learn neural network basics, architecture, hyperparameters, and implementation in Python using TensorFlow/Keras. Includes hands-on coding examples for various classification tasks, from simple to complex datasets.
YOLOv8 Object Detection - First Look Live Coding
Explore YOLOv8 for object detection in Python, from installation to implementation on images, webcams, and videos. Includes hands-on coding and practical demonstrations.
Face Detection with Python - Live Coding
Explore Python face detection models for age, race, emotion, and keypoints. Compare results and implement various techniques in this hands-on coding session.
Solving an Impossible Riddle with Code
Explore Python coding to simulate and solve the 100 prisoner riddle, comparing random and loop strategies through data visualization and network analysis.
Time Series Forecasting with XGBoost - Use Python and Machine Learning to Predict Energy Consumption
Learn to predict energy consumption using XGBoost and Python in this hands-on tutorial. Covers data preparation, feature engineering, model building, and forecasting techniques for time series analysis.
Video Data Processing with Python and OpenCV
Learn to process video data using Python and OpenCV, covering reading, writing, metadata extraction, image manipulation, and annotation. Gain essential skills for machine learning applications in computer vision.
Complete Guide to Cross Validation
Comprehensive guide to cross-validation in machine learning, covering setup, datasets, common pitfalls, train-test splits, and practical applications using scikit-learn in Python.
Solving Real World Data Science Problems With Python - Computer Vision Edition
Learn to build and improve convolutional neural networks for computer vision tasks using Python, TensorFlow, and Keras. Explore data augmentation, preprocessing, and network architecture optimization techniques.
How to Implement Autoencoders in Python and Keras - The Decoder
Learn to implement the decoder component of autoencoders using Python, TensorFlow, and Keras. Covers building methods, layers, and architecture for generating sound with neural networks.
How to Implement Autoencoders in Python and Keras - The Encoder
Learn to implement autoencoders in Python and Keras, focusing on building the encoder component. Covers autoencoder class construction, convolutional layers, bottleneck creation, and practical implementation.
Build a Spotify-Like Music Recommender System in Python
Create a Spotify-like music recommender system using Python, collaborative filtering, and Alternating Least Squares. Learn about music recommendation types, Spotify's architecture, and implement artist suggestions with the 'implicit' library.
Implementing and Training a Neural Network with PyTorch
Build and train a feed-forward neural network using PyTorch to classify MNIST digits. Learn data management, network implementation, and training loop creation in this hands-on tutorial.
Preprocessing Audio Datasets for Machine Learning
Build an audio preprocessing pipeline for AI in Python, covering STFT, zero-padding, and min-max normalization. Learn to batch process audio files efficiently for machine learning applications.