Anshu Trivedi's Projects
Prediction of success of google play apps.
A Python framework for program synthesis with a focus on Automated Machine Learning.
Bertelsmann Tech Scholarship Challenge Course - AI Track Nanodegree Program exercises and notes
In this project , we are working on making ML model which can predict price of old and used cars .
In this repository all the three projects completed in computer vision nano degree are available.Projects are Facial keypoint detection, Image captioning, Landmark Detection & Robot Tracking (SLAM).
Coursera Assignment Solutions
Submit all your blueprints in this repository with a folder of your team name
Data Analyst Track from Dataquest containing complete my course notes,projects in this repository.
This repository contains notes and projects of Data scientist track from dataquest course work.
Deep Learning Specialization- Coursera assignments, projects and notes
Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101
Python package for graph statistics
High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
This repository contains detailed notes of all chapters and all three projects completed in Intel-Edge-AI NanoDegree.
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
This repository contains projects and exercises of Machine Learning Scientist With Python course from DataCamp .
A repository to keep all open sources projects that created by individuals or study groups of Microsoft ML Scholarship
E2E test framework for tests with complex environment requirements.
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.