Chaithanya Kumar A's Projects
This Project is all about building a DL pipeline to process the real world, user-supplied Images. Given an image of a dog the algorithm will identify an estimate of the canineโs breed. If supplied with an image of a human, the code will identify the resembling dog breed.
This Project is all about building a Deep Learning Pipe Line to process the real world , user supplied Images. Given an Image of a dog the algorithm will identify an estimate of the canineโs breed. If supplied an image of a human, the code will identify the resembling dog breed.(TensorFlow Version)
This project will be all about defining and training a convolutional neural network to perform facial keypoint detection, and using computer vision techniques to transform images of faces.
TensorFlow CNN for fast style transfer โก๐ฅ๐จ๐ผ
The fastai deep learning library, plus lessons and tutorials
Draft of the fastai book
A faster pytorch implementation of faster r-cnn
Google Cloud tutorial and setup
This Repo Includes all the Google Cloud Command Line Interfaces important command lines along with several other important References.
This Project is all about defining and training a DCGAN on a dataset of faces. The goal of the project is to get a generator network to generate new images of faces that look as realistic as possible!
$ git remote <graduation> yearbook
Always know what to expect from your data.
this repository accompanies the book "Grokking Deep Learning"
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
Image Caption Generator project focuses on creating a Neural Network architecture to automatically generate captions from images.
Basic Image Segmentation on the Oxford IIT Pet Dataset Using State of the Art Image Segmentation Algorithm UNET
Instant Image Segmentation using state of the art Deep Learning Architecture Mask RCNN and FaceBook AI Research Detectron-2 API On a Custom Dataset
A packaged and flexible version of the CRAFT text detector and Keras CRNN recognition model.
Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).
Lime: Explaining the predictions of any machine learning classifier
A booklet on machine learning systems design with exercises
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
Fast, modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch.
Tutorials, assignments, and competitions for MIT Deep Learning related courses.
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
Models and examples built with TensorFlow
MIT Deep Learning 6S191 Assignment Solutions.
Building and Training a Artificial Neural Network(ANN) From Scratch To Predict The Number Of BikeShare Users On a Given Day.
Problem Solving with Algorithms and Data Structures using Python
A collection of full-stack resources for programmers.