yugaljain1999 Goto Github PK
Name: Yugal Jain
Type: User
Bio: Data Science | Deep Learning | Natural Language Processing
Twitter: biased_ai
Location: India
Name: Yugal Jain
Type: User
Bio: Data Science | Deep Learning | Natural Language Processing
Twitter: biased_ai
Location: India
Deep Learning has emerged as a new area in machine learning and is applied to a number of image applications. The main purpose of the this work is to apply the concept of a Deep Learning algorithm namely, Convolutional neural networks (CNN) in image classification. The algorithm is tested on standard COCO datasets. The performance of the algorithm is evaluated based on the quality metric known as Mean Squared Error (MSE) and classification accuracy. The experimental result analysis based on the quality metrics and the graphical representation proves that the algorithm (CNN) gives fairly good classification accuracy for all the tested datasets. Then we used visualization technique on the particular image for understanding which part of a given image led to convert to its final classification decision. For this we used CAM Visualisation technique. We also tried in doing object detection by using Pytorch.
Animal Sounds Machine Learning
Implementations for a family of attention mechanisms, suitable for all kinds of natural language processing tasks and compatible with TensorFlow 2.0 and Keras.
Generating Captions for images using Deep Learning
A curated list of awesome Machine Learning frameworks, libraries and software.
a facebook messenger bot that allows users to chat with other people on facebook anonymously
Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch
ACL 2020 Unsupervised Opinion Summarization as Copycat-Review Generation
Stanford CoreNLP: A Java suite of core NLP tools.
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This is the code for "DeepFakes" by Siraj Raval on Youtube
A collection of various deep learning architectures, models, and tips
Open Source for Deep Neural Network Compiler for All Platforms
Colab Notebooks covering all learning objectives of DS Unit4
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
Speedy Wavenet generation using dynamic programming :zap:
GeDi: Generative Discriminator Guided Sequence Generation
A high performance topological machine learning toolbox in Python
$ git remote <graduation> yearbook
BERT + Image Captioning
A declarative, efficient, and flexible JavaScript library for building user interfaces.
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TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
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A PHP framework for web artisans
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Open source projects and samples from Microsoft.
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Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.