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a-pytorch-tutorial-to-image-captioning

Show, Attend, and Tell | a PyTorch Tutorial to Image Captioning

ai-for-good-specialization

Learn AI's role in addressing complex challenges. Build skills combining human and machine intelligence for positive real-world impact using AI

angularjs-contact-app

https://javabrains.io/courses/angularjs_services

annotated-transformer

An annotated implementation of the Transformer paper.

awesome-datamesh

building-systems-with-the-chatgpt-api

In Building Systems With The ChatGPT API, you will learn how to automate complex workflows using chain calls to a large language model.

caffe

Caffe: a fast open framework for deep learning.

chatgpt-prompt-engineering-for-developers

In ChatGPT Prompt Engineering for Developers, you will learn how to use a large language model (LLM) to quickly build new and powerful applications.

cornell-cs5785-2023-applied-ml

Lecture materials for Cornell CS5785 Applied Machine Learning (Fall 2023)

course-api-data

https://javabrains.io/courses/spring_bootquickstart/ Spring Data JPA

crwn-clothing

Learning React

cs228-material

Teaching materials for the probabilistic graphical models and deep learning classes at Stanford

data-engineering

databricks-fernet-udf

deeplearning-pytorch

deepunderstandingofdeeplearning

Python code accompanying the course "A deep understanding of deep learning (with Python intro)"

dlib

A toolkit for making real world machine learning and data analysis applications in C++

evaluating-and-debugging-generative-ai

Machine learning and AI projects require managing diverse data sources, vast data volumes, model and parameter development, and conducting numerous test and evaluation experiments. Overseeing and tracking these aspects of a program can quickly become an overwhelming task.

flask-example

gdl_code

The official code repository for examples in the O'Reilly book 'Generative Deep Learning'

geeksforgeeks

generative-ai-with-llms

In Generative AI with Large Language Models (LLMs), you’ll learn the fundamentals of how generative AI works, and how to deploy it in real-world applications.

graph-data-science-with-neo4j

Graph Data Science with Neo4j, Published by Packt

hibernatespringboot

MySQL hibernating

how-diffusion-models-work

In How Diffusion Models Work, you will gain a deep familiarity with the diffusion process and the models which carry it out. More than simply pulling in a pre-built model or using an API, this course will teach you to build a diffusion model from scratch.

jdbcdemo

https://javabrains.io/courses/spring_data/

jetson-ml-containers

docker with jetson devices

kalman-and-bayesian-filters-in-python

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.

langchain-chat-with-your-data

Start building practical applications that allow you to interact with data using LangChain and LLMs.

langchain-for-llm-application-development

In LangChain for LLM Application Development, you will gain essential skills in expanding the use cases and capabilities of language models in application development using the LangChain framework.