Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
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Updated
Feb 2, 2024 - HTML
Deep neural networks (DNNs) are a class of artificial neural networks (ANNs) that are deep in the sense that they have many layers of hidden units between the input and output layers. Deep neural networks are a type of deep learning, which is a type of machine learning. Deep neural networks are used in a variety of applications, including speech recognition, computer vision, and natural language processing. Deep neural networks are used in a variety of applications, including speech recognition, computer vision, and natural language processing.
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
A Simple and easy to use way to Visualise Embeddings!
The project surveys 16+ Natural Language Processing (NLP) research papers that propose novel Deep Neural Network Models for Text Classification, based on Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN). It also implements each of the models using Tensorflow and Keras.
Fake News Detection using Deep Learning models in Tensorflow
In this project, I used Python and TensorFlow to classify traffic signs. Dataset used: German Traffic Sign Dataset. This dataset has more than 50,000 images of 43 classes. I was able to reach a +99% validation accuracy, and a 97.3% testing accuracy.
AI Learning Hub for Machine Learning, Deep Learning, Computer Vision and Statistics
Documentation for Deeplearning4j - Deep Learning for the JVM, Java & Scala
🐵 An AI chess-board-game framework(by many programming languages) implementations.
Face detection from webcam in browser using javascript library face-api.js
Voicegain Enterprise Speech-to-Text Platform (API, Portal, etc.)
webpage for maintaining the list of openly available DL, ML, RL, Vision, NLP, Optimization courses
Mixture of experts on convolutional neural network using Keras and Cifar10
Experiments on cluttered mnist dataset with Tensorflow.
We aim to generate realistic images from text descriptions using GAN architecture. The network that we have designed is used for image generation for two datasets: MSCOCO and CUBS.
Dog Breed classifier project of the Data Scientist Nanodegree by Udacity. A Web Application is developed using Flask through which a user can check if an uploaded image is that of a dog or human. Also, if the uploaded image is that of a human, the algorithm tells the user what dog breed the human resembles the most. The Deep Learning model disti…
Dataset Analysis & CNN Models Optimization for Plant Disease Classification.
This repository contains code and bonus content which will be added from time to time for the books "Learning Generative Adversarial Network- GAN" and "R Data Analysis Cookbook - 2nd Edition" by Packt
A simple approach to perform basic ML algorithms from scratch.
Deep learning utility library for natural language processing
AI based health checkup web tool