I am an experienced data scientist & engineer with more than 10 years of experience building large scale machine learning and data analytics platforms and solutions. I am currently an AI/ML specialist engineer at Google Cloud.
Connect:
Name: Nishit
Type: User
Company: @google
Bio: Data & Machine Learning
Location: Tampa, Florida
100 Days of ML Coding
100 data puzzles for pandas, ranging from short and simple to super tricky (60% complete)
Example notebooks that show how to apply machine learning and deep learning in Amazon SageMaker
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
A curated list of awesome places to learn and/or practice algorithms.
A curated list of awesome computer vision resources
A curated list of awesome Deep Learning tutorials, projects and communities.
A curated list of resources for learning about Google Cloud Platform certifications and how to prepare for it.
Interesting links & research papers related to Machine Learning applied to source code
:book: A curated list of resources dedicated to Natural Language Processing (NLP)
Repository containing the Articles on azure.microsoft.com Documentation Center
Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1
Class Assignments for UIUC 598 Practical Statistical Learning
Cracking the Coding Interview 6th Ed. Python Solutions
Python solutions to Cracking the Coding Interview (6th edition)
Visualization of Every Satellite Orbiting The Earth in D3.js
Cheat Sheets
List of Data Science and Machine Learning Resource that I frequently use
A curated list of data science blogs
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
Source code accompanying book: Data Science on the Google Cloud Platform, Valliappa Lakshmanan, O'Reilly 2017
Examples and illustration of basic statistic concepts, probability distribution, Monte Carlo simulation, preprocessing and visualization techniques, and statistical testing.
Assignmends done for Udacity's Deep Learning MOOC with Vincent Vanhoucke
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
Survival analsyis and time-to-failure predictive modeling using Weibull distributions and Recurrent Neural Networks in Keras
Collection of Ebooks (pdf)
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.