Himanshu Goyal's Projects
An interface to select the best suited image for a given word
List of good resources to automate the co-win registration process
#Tensorflow #keras based implementation of the #CycleGAN paper. This utilizes the network created from the keras functionality included in the tensorflow.
Check out the live demo at below link, username : [email protected], pass: testing1234
My personal blog and info website
Advanced experiments and research paper implementation for Knowledge distillation
Live Demo(takes 3-4 minutes to load) : https://Im-Himanshu.github.io/LiveFaceDetection-TensorFlowJs/ this app recognize the faces in the camera input and predict the expression like neutral,angry etc. utilizes tensorflowJs model to load the train model in memory
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.
This is four player ping pong ball game with one player on each side of the square, each player can join over the network like the CS GO. Also has a adoptive computer-player feature to challenge you.
My Experiments with latest NLP algorithms, implemented in Tensorflow. Following general Article on internet, Too Lazy to give formal references but I also don't claim this work to be mine orginally. ThankYou Internet for all the help.
scrapping movie data from paytm using selenium in python
My resume in pdf. Hosted on a URL linked in resume and other places.
Material for tomorrow's full data training for CITI's bridge program. This is the project we will be building in tomorrow's live session.
for helping people building the vocab from the book or the novel they have read by feeding it to the algorithm which will filter out hard word from it
Multi-platform (ios/Android/web) Application to help building vocabulary for different examinations using some of the best and scientifically proven methods of building linguistic memory.
BTP project for automating the tedious process of yarn-cross section analysis using ML. Will be implementing various algorithm (CNN, ANN etc..) to see what works best. This also has a python program for enable user to draw images, used as database for algorithm.
YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/