AI-For-Beginners
12 Weeks, 24 Lessons, AI for All!
Discover Large Language Models LLMs like GPT prompt programming and few-shot learning for beginners Learn how to use text prompts and examples to guide powerful AI models without extensive training.
How to Perform Named Entity Recognition (NER) Using TensorFlow in AI-For-BeginnersLearn how to perform Named Entity Recognition NER using TensorFlow with the AI For Beginners implementation. Explore Bidirectional LSTM and TimeDistributed dense layers for token classification.
How Transformers and BERT Work: Understanding Attention Mechanisms in AI for BeginnersUnderstand how Transformers and BERT work using attention mechanisms. Explore AI for Beginners and unlock the power of parallel processing and bidirectional encoding for deep language understanding.
How to Generate Text Using RNNs in AI for Beginners: A Complete Implementation GuideLearn to generate text with RNNs in AI for beginners. This guide covers SimpleRNN and LSTM for predicting text based on context. Start your AI journey now.
LSTM and GRU Architectures for Recurrent Neural Networks: A Beginner's GuideMaster LSTM and GRU for Recurrent Neural Networks. Learn how these AI architectures handle long-range dependencies and solve vanishing gradients in sequential data.
How to Train Custom Word Embeddings Using CBoW in PyTorch: AI-For-Beginners GuideLearn to train custom word embeddings with CBoW in PyTorch. This AI for Beginners guide shows how to create vector representations for your NLP projects.
How Word2Vec and GloVe Embeddings Are Used in NLP: Microsoft AI-For-Beginners GuideLearn how Word2Vec and GloVe embeddings power NLP with the Microsoft AI-For-Beginners guide. Explore CBoW Skip-Gram and pre-trained vector integration.
How to Represent Text Using Bag-of-Words and TF-IDF in PyTorchLearn to represent text with Bag-of-Words and TF-IDF in PyTorch using Microsoft's AI for Beginners. Convert text to numerical tensors for AI models.
Semantic Segmentation with U-Net in PyTorch: Implementation Guide for AI for BeginnersLearn semantic segmentation with U-Net in PyTorch. Implement this encoder-decoder model for image segmentation using the AI-For-Beginners repository. Perfect for beginners!
How Does Object Detection with YOLO Work in Microsoft's AI for Beginners?Understand object detection with YOLO in Microsoft's AI for Beginners. Learn how YOLO predicts bounding boxes and class probabilities efficiently in one forward pass.
How GANs Enable Artistic Style Transfer in the AI-For-Beginners CurriculumLearn how Generative Adversarial Networks (GANs) power artistic style transfer in the Microsoft AI-For-Beginners curriculum. Explore U-Net, PatchGAN, and loss functions.
How Autoencoders and VAEs Work for Image Compression in AI for BeginnersLearn how autoencoders and VAEs achieve image compression in AI. Discover how these models encode and decode data for efficient reconstruction.
Have a question about this repo?
These articles cover the highlights, but your codebase questions are specific. Give your agent direct access to the source. Share this with your agent to get started:
curl -s "https://instagit.com/install.md" 
Maintain an open-source project? Get it listed too →