iPython NotebooksCheat Sheets / References, Learning Guides, Etc. / Tutorial
From GitHub: “This repo contains various iPython notebooks I’ve created to experiment with libraries and work through exercises, and explore subjects that I find interesting.” The notebooks include: Popular Python data science libraries NumPy SciPy Matplotlib Pandas Statsmodels Scikit-learn Seaborn NetworkX PyMC NLTK DEAP Genism Machine Learning Exercises Tensorflow Deep Learning Exercises Spark Big Data Labs Miscellaneous
Python for Data Science and Machine Learning BootcampCourses / Self-paced online course
From Udemy: “Learn how to use NumPy, Pandas, Seaborn, Matplotlib, Plotly, Scikit-Learn, Machine Learning, Tensorflow, and more! What Will I Learn? Use Python for Data Science and Machine Learning Use Spark for Big Data Analysis Implement Machine Learning Algorithms Learn to use NumPy for Numerical Data Learn to use Pandas for Data Analysis Learn to use Matplotlib for Python Plotting Learn to use Seaborn for statistical plots Use Plotly for interactive … Continue Reading
NumPy Cheat Sheet – Python for Data ScienceCheat Sheets / References, Learning Guides, Etc.
“It’s common when first learning NumPy to have trouble remembering all the functions and methods that you need, and while at Dataquest we advocate getting used to consulting the NumPy documentation, sometimes it’s nice to have a handy reference, so we’ve put together this cheat sheet to help you out.” This cheat sheet covers the following topics: Key and Imports Importing/Exporting Creating Arrays Inspecting Properties Copying/sorting/reshaping Adding/removing Elements Combining/splitting Indexing/slicing/subsetting Scalar Math … Continue Reading
Comprehensive learning path – Data Science in PythonCurricula / References, Learning Guides, Etc.
From Analytics Vidhya: “So, you want to become a data scientist or may be you are already one and want to expand your tool repository. You have landed at the right place. The aim of this page is to provide a comprehensive learning path to people new to python for data analysis. This path provides a comprehensive overview of steps you need to learn to use Python for data analysis. … Continue Reading
Python Data Science Handbook: Essential Tools for Working with DataBooks / physical books or multiple formats
From Amazon: “For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this … Continue Reading
DataCamp – pandas FoundationsCourses / Interactive tutorial style course
From DataCamp: “Many real-world data sets include strings, integers, time-stamps and unstructured data. How do you store data like this so that you can manipulate it and easily retrieve important information? The answer is in a pandas DataFrame! In this course, you’ll learn how to use the industry-standard pandas library to import, build, and manipulate DataFrames. With pandas, you’ll always be able to convert your data into a form that permits … Continue Reading
DataCamp – Intro to Python for Data ScienceCourses / Interactive tutorial style course
From DataCamp: “Python is a general-purpose programming language that is becoming more and more popular for doing data science. Companies worldwide are using Python to harvest insights from their data and get a competitive edge. Unlike any other Python tutorial, this course focuses on Python specifically for data science. In our Intro to Python class, you will learn about powerful ways to store and manipulate data as well as cool data … Continue Reading
DataQuest – Python Programming: Intermediate CourseCourses / Interactive tutorial style course
This course is step 2 of 6 in the DataQuest Data Analyst Path and step 2 of 11 in the DataQuest Data Scientist Path. From DataQuest: “Learn some more aspects of Python, including modules, enumeration, indexing, and scopes. What you’ll learn: Learn how to create modules and classes to organize your code Learn how to handle errors, use list comprehensions, and use regular expressions Learn about variable scoping and the date … Continue Reading
Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPythonBooks / physical books or multiple formats
This is a book about the parts of the Python language and libraries you’ll need to effectively solve a broad set of data analysis problems.