Rishabh Goyal's repositories
semantic-segmentation-pytorch
Pytorch implementation for Semantic Segmentation/Scene Parsing on MIT ADE20K dataset
arxiv-sanity-preserver
Web interface for browsing, search and filtering recent arxiv submissions
azure-iot-sdk-c
A C99 SDK for connecting devices to Microsoft Azure IoT services
azure-iot-sdk-csharp
A C# SDK for connecting devices to Microsoft Azure IoT services
azure-sdk-for-go
Microsoft Azure SDK for Go
azure-storage-net
Microsoft Azure Storage Libraries for .NET
CarND-LaneLines-P1
Lane Finding Project for Self-Driving Car ND
DataFrame
This is a C++ statistical library to provide an interface similar to Pandas package in Python
docker-cheat-sheet
Docker Cheat Sheet
handson-ml
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
json
JSON for Modern C++
machine-learning
Content for Udacity's Machine Learning curriculum
og-aws
📙 Amazon Web Services — a practical guide
opencv
Open Source Computer Vision Library
P1_Facial_Keypoints
First project for CVND: facial keypoint detection.
Plotly-Dashboards-with-Dash
This is the repo for the Udemy Course Python Dashboards with Plotly's Dash
Processing-Big-Data-with-Hadoop-in-Azure-HDInsight
Shared files for Processing Big Data with Hadoop in Azure HDInsight course
Product-Recommendations
Product Recommendations solution
python-sdk
:snake: Client library to use the IBM Watson services in Python and available in pip as watson-developer-cloud
really-awesome-semantic-segmentation
A list of papers on Semantic Segmentation.
self-driving-car-1
Udacity Self-Driving Car Engineer Nanodegree projects.
self-driving-car-nd
Udacity's Self-Driving Car Nanodegree project files and notes.
swirl_courses
:mortar_board: A collection of interactive courses for the swirl R package.
vehicle_signal_specification
Vehicle Signal Specification standard building on the work done by W3C / AMB.
vs-tools-for-ai
Visual Studio Tools for AI is a free Visual Studio extension to build, test, and deploy deep learning / AI solutions. It seamlessly integrates with Azure Machine Learning for robust experimentation capabilities, including but not limited to submitting data preparation and model training jobs transparently to different compute targets. Additionally, it provides support for custom metrics and run history tracking, enabling data science reproducibility and auditing. Enterprise ready collaboration, allow to securely work on project with other people.