New Machine Learning Cheat Sheet by Emily Barry

New #MachineLearning Cheat Sheet by Emily Barry #abdsc

  • This blog about machine learning was written by Emily Barry.
  • Emily is a Data Scientist in San Francisco, California.
  • The more she learns about machine learning algorithms, the more challenging it is to keep these subjects organized in her brain to recall at a later time.
  • This is by no means a comprehensive guide to machine learning, but rather a study in the basics for herself and the likely small overlap of people who like machine learning and love emoji as much as she do.
  • For more articles about machine learning, click here.

This blog about machine learning was written by Emily Barry. Emily is a Data Scientist in San Francisco, California. She really loves emoji. Another thing she…
Continue reading “New Machine Learning Cheat Sheet by Emily Barry”

Book: Machine Learning Algorithms From Scratch

Book: #MachineLearning Algorithms From Scratch #abdsc

  • From First Principles With Pure Python and

    Use them on Real-World Datasets

    You must understand algorithms to get good at machine learning.

  • In this mega Ebook written in the friendly Machine Learning Mastery style that you’re used to, finally cut through the math and learn exactly how machine learning algorithms work.
  • I’ve written books on algorithms, won and ranked in the top 10% in machine learning competitions, consulted for startups and spent a long time working on systems for forecasting tropical cyclones.
  • (yes I have written tons of code that runs operationally)

    I get a lot of satisfaction helping developers get started and get really good at machine learning.

  • I teach an unconventional top-down and results-first approach to machine learning where we start by working through tutorials and problems, then later wade into theory as we need it.

Discover How to Code Machine Algorithms
From First Principles With Pure Python and
Use them on Real-World Datasets

$37 USD
You must understand algorithms t…
Continue reading “Book: Machine Learning Algorithms From Scratch”

New Machine Learning Cheat Sheet by Emily Barry

Machine Learning Cheat Sheet

  • This blog about machine learning was written by Emily Barry.
  • Emily is a Data Scientist in San Francisco, California.
  • The more she learns about machine learning algorithms, the more challenging it is to keep these subjects organized in her brain to recall at a later time.
  • This is by no means a comprehensive guide to machine learning, but rather a study in the basics for herself and the likely small overlap of people who like machine learning and love emoji as much as she do.
  • For more articles about machine learning, click here.

This blog about machine learning was written by Emily Barry. Emily is a Data Scientist in San Francisco, California. She really loves emoji. Another thing she…
Continue reading “New Machine Learning Cheat Sheet by Emily Barry”

Python for Big Data in One Picture

Python for Big Data in One Picture  #DataScience #IoT #MachineLearning #BigData

  • This picture originally posted here covers the following topics:

    To zoom in, view picture in the original article, or click on picture.

  • The original article also provides a detailed listing of all the 100+ entities listed in the picture, broken down in categories and sub-categories, some items belonging to multiple categories.
  • Anyone interested in creating a clickable link for each of these entities?
  • For instance, entity 1.1 (in the original article) is numpy, while 4.1 is matplotlib.

This picture originally posted here covers the following topics:

Basic stack
Newer packages
Integrated platforms
Visualization
Data formats
MapReduce
Glue
GPU…
Continue reading “Python for Big Data in One Picture”

New Machine Learning Cheat Sheet by Emily Barry

Machine Learning Cheat Sheet

  • This blog about machine learning was written by Emily Barry.
  • Emily is a Data Scientist in San Francisco, California.
  • The more she learns about machine learning algorithms, the more challenging it is to keep these subjects organized in her brain to recall at a later time.
  • This is by no means a comprehensive guide to machine learning, but rather a study in the basics for herself and the likely small overlap of people who like machine learning and love emoji as much as she do.
  • For more articles about machine learning, click here.

This blog about machine learning was written by Emily Barry. Emily is a Data Scientist in San Francisco, California. She really loves emoji. Another thing she…
Continue reading “New Machine Learning Cheat Sheet by Emily Barry”

Book: Evaluating Machine Learning Models

Book: Evaluating #MachineLearning Models #abdsc

  • If you’re new to data science and applied machine learning, evaluating a machine-learning model can seem pretty overwhelming.
  • With this O’Reilly report, machine-learning expert Alice Zheng takes you through the model evaluation basics.
  • In this overview, Zheng first introduces the machine-learning workflow, and then dives into evaluation metrics and model selection.
  • With this report, you will:

    Alice is a technical leader in the field of Machine Learning.

  • Previous roles include Director of Data Science at GraphLab/Dato/Turi, machine learning researcher at Microsoft Research, Redmond, and postdoctoral fellow at Carnegie Mellon University.

Data science today is a lot like the Wild West: there’s endless opportunity and excitement, but also a lot of chaos and confusion. If you’re new to data scien…
Continue reading “Book: Evaluating Machine Learning Models”

Book: Machine Learning Algorithms From Scratch

Book: Machine Learning Algorithms From Scratch | #BigData #MachineLearning #RT

  • From First Principles With Pure Python and

    Use them on Real-World Datasets

    You must understand algorithms to get good at machine learning.

  • In this mega Ebook written in the friendly Machine Learning Mastery style that you’re used to, finally cut through the math and learn exactly how machine learning algorithms work.
  • I’ve written books on algorithms, won and ranked in the top 10% in machine learning competitions, consulted for startups and spent a long time working on systems for forecasting tropical cyclones.
  • (yes I have written tons of code that runs operationally)

    I get a lot of satisfaction helping developers get started and get really good at machine learning.

  • I teach an unconventional top-down and results-first approach to machine learning where we start by working through tutorials and problems, then later wade into theory as we need it.

Discover How to Code Machine Algorithms
From First Principles With Pure Python and
Use them on Real-World Datasets

$37 USD
You must understand algorithms t…
Continue reading “Book: Machine Learning Algorithms From Scratch”