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This article covers the top 5 data science and machine learning GitHub repositories and Reddit discussions from February 2019.
In this semantic segmentation tutorial, learn image segmentation concepts and build a semantic segmentation model using Python. Start Now!
Crowd counting has been an inexact science for decades. Learn about crowd counting algorithms in deep learning and build crowd counting models using python.
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.
This article is inspired by Deeplearning.ai course where we learn to solve sequence modeling problems and building attention models.
An introduction to pytorch and pytorch build neural networks. Get started with pytorch, how it works and learn how to build a neural network.
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