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10-steps-to-become-a-data-scientist

📢 Ready to learn! you will learn 10 skills as data scientist:📚 Machine Learning, Deep Learning, Data Cleaning, EDA, Learn Python, Learn python packages such as Numpy, Pandas, Seaborn, Matplotlib, Plotly, Tensorfolw, Theano...., Linear Algebra, Big Data, Analysis Tools and solve some real problems such as predict house prices.

120-data-science-interview-questions

Answers to 120 commonly asked data science interview questions.

alfred-workflows

:metal: A collection of Alfred 3 workflows that will rock your world

archery

2D R-Tree implementation in Scala

awesome-falsehood

:pill: Curated list of falsehoods programmers believe in.

awesome-geospatial

Long list of geospatial tools and resources

awesome-machine-learning

A curated list of awesome Machine Learning frameworks, libraries and software.

awesome-rnn

Recurrent Neural Network - A curated list of resources dedicated to RNN

awesome-speech-recognition-speech-synthesis-papers

Automatic Speech Recognition, Speaker Verification, Speech Synthesis, Language Modeling

awesome-tensorflow

TensorFlow - A curated list of dedicated resources http://tensorflow.org

bayadera

High-performance Bayesian Data Analysis on the GPU in Clojure

beaker-notebook-archive

Archive of Beaker Notebook

beakerx

Beaker Extensions for Jupyter Notebook

chronix.spark

Time series analysis with Apache Spark based on Chronix |

circles-sines-signals

A Compact Primer on Digital Signal Processing

codesignal-solutions

CodeSignal Solutions

coding-interview-university

A complete computer science study plan to become a software engineer.

commuter

🚎 share, publish, and discover notebooks

config

cryptopals

Cryptopals Crypto Challenges

dash-sample-apps

Apps hosted in the Dash Gallery

data-science-ipython-notebooks

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.

datashader

Turns even the largest data into images, accurately

deck.gl

WebGL based visualization layers

deeplearningbook

MIT Deep Learning Book in PDF format

dem-debate-2020-nlp

NLP on Democratic Debates for President 2020

dev-setup

Mac OS X development environment setup: Easy-to-understand instructions with automated setup scripts for developer tools like Vim, Sublime Text, Bash, iTerm, Python data analysis, Spark, Hadoop MapReduce, AWS, Heroku, JavaScript web development, Android development, common data stores, and dev-based OS X defaults.

docker-stacks

Opinionated stacks of ready-to-run Jupyter applications in Docker.

dotfiles

.files and ~/.macos

ds-take-home

My solution to the book A Collection of Data Science Take-Home Challenges