Deep Learning: From Perceptron to Large Language Models

Colleagues, in the Deep Learning: From Perceptron to Large Language Models program you will understand the essential building blocks of deep neural networks, such as artificial neurons and fully connected, convolutional, recurrent layers, how to build advanced architectures, including the Transformer, TensorFlow and encoders. He describes how these concepts are used to build modern networks for computer vision and Natural Language Processing (NLP), including large language models and multimodal networks. The code repository is located on github.com/NVDLI/LDL. Learn how to Apply core concepts of perceptrons, gradient-based learning, sigmoid neurons, and backpropagation, Utilize DL frameworks to make it easier to develop more complicated and useful neural networks, Utilize convolutional neural networks (CNNs) to perform image classification and analysis, Apply recurrent neural networks (RNNs) and long short-term memory (LSTM) to text and other variable-length sequences, Build a natural language translation application using sequence-to-sequence networks based on the transformer architecture, Use the transformer architecture for other natural language processing (NLP) tasks, and how to engineer prompts for large language models (LLM), and Combine image and text data and build multimodal networks, including an image captioning application. Skill-based lessons cover: 1) Deep Learning Introduction, 2) Neural Network Fundamentals I & II, 3) Convolutional Neural Networks (CNN) and Image Classification, 4) Recurrent Neural Networks (RNN) and Time Series Prediction, 5) Neural Language Models and Word Embeddings, 6) Encoder-Decoder Networks, Attention, Transformers, and Neural Machine Translation, 7) Large Language Models, 8) Multi-modal Networks and Image Captioning, 9) Multi-task Learning and Computer Vision Beyond Classification, and 10) Applying Deep Learning.

Enroll today (teams & execs welcome): https://tinyurl.com/47bs2k86 

Download your free AI-ML-DL - Career Transformation Guide.

For your listening-reading pleasure:

1 - “AI Software Engineer: ChatGPT, Bard & Beyond” (Audible) or (Kindle)  

2 - “ChatGPT - The Era of Generative Conversational AI Has Begun” (Audible) or (Kindle) 

3 - “ChatGPT, Gemini and Llama - The Journey from AI to AGI, ASI and Singularity” (Audible) or (Kindle) 

Much career success, Lawrence E. Wilson - AI Academy (share with your team)