Master Generative AI with 10+ Real-world Projects in 2025!
The top 5 data science GitHub repositories and Reddit discussions from January 2019. It includes links to awesome NLP and computer vision libraries.
StanfordNLP is a collection of pre-trained state-of-the-art models. This tutorial is an introduction to Stanford NLP in Python and its implementation.
Machine translation is one of the biggest applications of NLP. Learn about neural machine translation and its implementation in Python using keras.
Recurrent Neural Networks Python are one of the fundamental concepts of deep learning. Learn RNN from scratch and how to build and code.
Explore Game AI: Dive into AlphaGo, tree search algorithms, and Monte Carlo Tree Search (MCTS) for a deeper understanding of AI in gaming.
An introduction to pytorch and pytorch build neural networks. Get started with pytorch, how it works and learn how to build a neural network.
Build an image classification model in minutes without the need for powerful machines or extensive training. Discover the possibilities of deep learning.
An introduction to time series classification. In this article learn about its applications and how to build time series classification models with python.
Interested in deep learning but don’t know where to start? This article contains a learning path for deep learning to get started in 2019.
Complete learning path to become a data scientist in 2024. This article contains resources that will lead you down the path to be a data scientist.
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