Basic concepts

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Basic concepts

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Jupyter notebook environment execute, save and share code, from your browser

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Short and effective exercises

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Jupyter notebook environment execute, save and share code, from your browser

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Curated implementations of machine learning models in pytorch, tensor flow, caffe2, computer vision, natural language processing

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Blog aggregator, latest articles

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Command line tool to manage shared Python code and libraries

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Testing tool that helps you write better programs, pip install -U pytest

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Fundamental package for scientific computing, array and linear algebra functions

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High-level neural networks API, running on top of TensorFlow, CNTK, or Theano

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Open source deep learning platform that provides a seamless path from research prototyping to production deployment

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Data structures and data analysis tools

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Text processing libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning, working in computational linguistics

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Open-source, numerical computation

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Generate plots, histograms, power spectra, bar charts, errorcharts, scatterplots, etc.

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Learn Python directly inside a code editor

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Interpreted, high-level, general-purpose programming language

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Perform code on Linux, Windows, and Mac OS X

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Code editor

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Implementation of face recognition with deep neural networks

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Alternative to numpy and pandas that solves real-world problems with readable code

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Dataframe, read excel/csv, groupby,

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Data manipulation, cleaning analysis, pandas, Series and DataFrames, groupby, merge, and pivot tables, hypothesis testing

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Advanced topics about Python, introduction to NumPy and matrix multiplication

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Important computer science concepts, computation, simple algorithms, testing and debuggin, introduction to algorithmic complexity, data structures

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Fundamental programming concepts, syntax, control flow, lists, loops, strings, , modules, dictionaries, files, classes, function arguments

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Introduction to Programming, software development skills, data structures, Big-O notation, sorting & search algorithms,

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Principles of Information Visualization, basic charting with Matplotlib

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Code snippets on data manipulation, preprocessing, machine Learning, deep learning, statistics

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Manipulating, processing, cleaning, and crunching data with Pandas, NumPy, and IPython

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Concepts, algorithm and applications with Scikit-Learn, Keras, and TensorFlow

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Exploratory data analysis, distributions, probability mass functions, cumulative distribution functions, modeling, probability density functions, hypothesis testing

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Introduction to Numpy, Data Manipulation with Pandas, Visualization with Matplotlib, Machine Learning with Scikit-Learn

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Basic Python syntax, data types, language concepts, scrape websites and APIs, Python libraries, automate entire data-wrangling process

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*

Interpreted, high-level, general-purpose programming language

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*
*

Blog aggregator, latest articles

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*
*

Manipulating, processing, cleaning, and crunching data with Pandas, NumPy, and IPython

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*
*

Short and effective exercises

*Upvote*
*
*

Data manipulation, cleaning analysis, pandas, Series and DataFrames, groupby, merge, and pivot tables, hypothesis testing

*Upvote*
*
*

Concepts, algorithm and applications with Scikit-Learn, Keras, and TensorFlow

*Upvote*
*
*

Advanced topics about Python, introduction to NumPy and matrix multiplication

*Upvote*
*
*

Important computer science concepts, computation, simple algorithms, testing and debuggin, introduction to algorithmic complexity, data structures

*Upvote*
*
*

Exploratory data analysis, distributions, probability mass functions, cumulative distribution functions, modeling, probability density functions, hypothesis testing

*Upvote*
*
*

Learn Python directly inside a code editor

*Upvote*
*
*

Introduction to Numpy, Data Manipulation with Pandas, Visualization with Matplotlib, Machine Learning with Scikit-Learn

*Upvote*
*
*

Fundamental programming concepts, syntax, control flow, lists, loops, strings, , modules, dictionaries, files, classes, function arguments

*Upvote*
*
*

Dataframe, read excel/csv, groupby,

*Upvote*
*
*

Introduction to Programming, software development skills, data structures, Big-O notation, sorting & search algorithms,

*Upvote*
*
*

Basic Python syntax, data types, language concepts, scrape websites and APIs, Python libraries, automate entire data-wrangling process

*Upvote*
*
*

Principles of Information Visualization, basic charting with Matplotlib

*Upvote*
*
*

Jupyter notebook environment execute, save and share code, from your browser

*Upvote*
*
*

Fundamental package for scientific computing, array and linear algebra functions

*Upvote*
*
*

High-level neural networks API, running on top of TensorFlow, CNTK, or Theano

*Upvote*
*
*

Jupyter notebook environment execute, save and share code, from your browser

*Upvote*
*
*

Open source deep learning platform that provides a seamless path from research prototyping to production deployment

*Upvote*
*
*

Data structures and data analysis tools

*Upvote*
*
*

Text processing libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning, working in computational linguistics

*Upvote*
*
*

Curated implementations of machine learning models in pytorch, tensor flow, caffe2, computer vision, natural language processing

*Upvote*
*
*

Open-source, numerical computation

*Upvote*
*
*

Command line tool to manage shared Python code and libraries

*Upvote*
*
*

Generate plots, histograms, power spectra, bar charts, errorcharts, scatterplots, etc.

*Upvote*
*
*

Perform code on Linux, Windows, and Mac OS X

*Upvote*
*
*

Code snippets on data manipulation, preprocessing, machine Learning, deep learning, statistics

*Upvote*
*
*

Testing tool that helps you write better programs, pip install -U pytest

*Upvote*
*
*

Code editor

*Upvote*
*
*

Implementation of face recognition with deep neural networks

*Upvote*
*
*

Alternative to numpy and pandas that solves real-world problems with readable code

*Upvote*
*
*

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