I found an interesting websites featuring hundreds of charts derived from US census data. It shows contrasts between states, cities, regarding education, jobs, languages spoken, salaries, even discrepencies between men and women or Asians and Caucasians, regarding various metrics broken down by location, education, or other criteria. I selected four of these charts.…

ContinueAdded by Capri Granville on June 10, 2019 at 5:00pm — No Comments

This chart communicates the same insights as a contour plot. What is interesting is the choice of hexagonal buckets (rather than squares) to aggregate data. In fact, any tessellation would work, in particular Voronoi tessellations.…

ContinueAdded by Capri Granville on June 9, 2019 at 8:00am — 1 Comment

*Not to be confused with this free Microsoft book with same title.*

Data science underlies Amazon's product recommender, LinkedIn's People You Know feature, Pandora's personalized radio stations, Stripe's fraud detectors, and the incredible insights arising from the world's increasingly ubiquitous sensors. In the future,…

ContinueAdded by Capri Granville on May 23, 2019 at 9:00am — No Comments

I stumbled upon this book by chance, when searching for material about time series (probably the most interesting chapter in this collection.) The various chapters are accessible from the top tabs, on this web page. It is mostly about R, but it has a few interesting chapters on statistical science too. Below is a…

ContinueAdded by Capri Granville on May 23, 2019 at 9:00am — No Comments

*By Avrim Blum, John Hopcroft, and Ravindran Kannan (2018). *

Computer science as an academic discipline began in the 1960s. Emphasis was on programming languages, compilers, operating systems, and the mathematical theory that supported these areas. Courses in theoretical computer science covered finite automata, regular expressions, context-free languages, and computability. In the 1970s, the study of algorithms was added as an important component of…

ContinueAdded by Capri Granville on May 23, 2019 at 9:00am — No Comments

The following notes represent a complete, stand alone interpretation of Stanford's machine learning course presented by Professor Andrew Ng and originally posted on the ml-class.org website during the fall 2011 semester. The topics covered are shown below, although for a more detailed summary see lecture 19. The only content not covered here…

ContinueAdded by Capri Granville on May 23, 2019 at 9:00am — No Comments

A free online version of the second edition of the book based on Stat 110, *Introduction to Probability* by Joe Blitzstein and Jessica Hwang, is now available here. Print copies are available via CRC Press, Amazon, and…

Added by Capri Granville on May 23, 2019 at 8:30am — 1 Comment

This glossary defines general machine learning terms as well as terms specific to TensorFlow. Below is a small selection of the most popular entries. You can access this glossary here. For other related glossaries, follow this link.

- A/B testing
- activation…

Added by Capri Granville on May 23, 2019 at 8:30am — No Comments

Interesting cartoon featuring the decision tree used in medical diagnosis. To see other cartoons about data science, follow this link.…

ContinueAdded by Capri Granville on April 25, 2019 at 9:00am — 1 Comment

Lecture notes for the Statistical Machine Learning course taught at the Department of Information Technology, University of Uppsala (Sweden.) Updated in March 2019. Authors: Andreas Lindholm, Niklas Wahlström, Fredrik Lindsten, and Thomas B. Schön.

*Source: page 61 in these lecture notes…*

Added by Capri Granville on April 25, 2019 at 9:00am — No Comments

*Guest blog by Stephan Loyd.*

Hello everybody, this is my first post here, so forgive me if I screw it up.

Let me firstly introduce background of my work. Several years ago I landed onto a Perl job. It also involves some other languages like Python and R, but it was mainly Perl, until last year focus of my role switched and I still do some Perl but much less since then. I was a little…

ContinueAdded by Capri Granville on April 14, 2019 at 6:30pm — No Comments

This 12-page document lists hundreds of Excel functions and formulas, covering

- Lookup/Ref Functions
- String/Text Functions
- Date/Time Functions
- Math/Trig Functions
- Statistical Functions
- Logical Functions
- Information Functions
- Financial Functions
- Database Functions
- Engineering Functions
- File/Directory Functions
- Data Type Conv. Functions
- More Lookup…

Added by Capri Granville on April 7, 2019 at 6:30am — No Comments

*This is the fourth article in a* DeepTech Series* by Margaretta Colangelo and Dmitry Kaminskiy. **Dmitry Kaminskiy**, General Partner at Deep Knowledge Ventures, is based in London. Dmitry is Managing Trustee…*

Added by Capri Granville on April 4, 2019 at 10:30am — No Comments

Creating *Info We Trust* is a craft that puts the world into forms that are strong and true. It begins with maps, diagrams, and charts — but must push further than dry defaults to be truly effective. How do we attract attention? How can we offer audiences valuable experiences worth their time? How can we help people access complexity?…

Added by Capri Granville on April 3, 2019 at 8:00am — No Comments

I was comparing home prices in San Francisco between 1994 and 2018, and I noticed that it has increased by a factor 4 over 25 years. In the meanwhile, the inflation index increased by a factor 1.7 (see here.) I am not saying here that my sources are correct or wrong -- entire books have been written on the subject -- but instead, my purpose here is to show how some visualizations can be…

ContinueAdded by Capri Granville on March 10, 2019 at 5:00pm — 1 Comment

Here is one of the most viral videos about data science posted in the last few months, with over 500,000 views. I could not locate the original copy; I found it in a re-tweet by Kirk Borne. See link to the video below the picture. However, I was able to find who created it (Welcome.ai) and it turns out that they have a YouTube channel with plenty of even more interesting videos. To search these videos by keyword, click…

ContinueAdded by Capri Granville on February 27, 2019 at 3:30pm — No Comments

Below is an extract of a 10-page cheat sheet about data science, compiled by Maverick Lin. This cheatsheet is currently a reference in data science that covers basic concepts in probability, statistics, statistical learning, machine learning, deep learning, big data frameworks and SQL. The cheatsheet is loosely based off of *The Data Science Design Manual* by Steven S. Skiena and *An Introduction to Statistical Learning* by…

Added by Capri Granville on February 26, 2019 at 7:30pm — No Comments

This article is a solid introduction to statistical testing, for beginners, as well as a reference for practitioners. It includes numerous examples as well as illustrations and definitions for concepts such as rejecting the null hypothesis, one sample hypothesis testing, P-values, critical values, and Bayesian hypothesis testing. It has references to additional topics, such as

- What is Ad Hoc Testing?
- What is a Rejection Region?
- What is a Two Tailed…

Added by Capri Granville on February 19, 2019 at 9:30am — No Comments

This infographic was produced by 365DataScience. Last year they completed a research on 1,001 data scientists to get a profile of the ‘typical’ data scientist in 2018. They replicated the study with new data. Below are the findings.

**Here are some of our key findings**:…

Added by Capri Granville on February 9, 2019 at 10:30am — 1 Comment

Below is an extract of a 10-page cheat sheet about probability, compiled by William Chen (http://wzchen.com) and Joe Blitzstein, with contributions from Sebastian Chiu, Yuan Jiang, Yuqi Hou, and Jessy Hwang. Material based on Joe Blitzstein’s Harvard's introductory probability course (@stat110 - (http://stat110.net) and Blitzstein / Hwang’s Introduction to Probability textbook (…

ContinueAdded by Capri Granville on February 3, 2019 at 8:00am — No Comments

- Interesting Charts and Maps Obtained Using Census Data
- Interesting Type of Chart: Hexagonal Binning
- Upcoming Book: Foundations of Data science
- Free Book: Statistics, Dataviz, and Data Cleaning with R
- Free Book: Foundations of Data Science (from Microsoft Research Lab)
- Lecture Notes by Andrew Ng : Full Set
- Free Textbook: Probability Course, Harvard University (Based on R)

- Traditional Programming versus Machine Learning, in One Picture
- Which Programming Language to Choose?
- New Data Science Cheat Sheet, by Maverick Lin
- Free Book: Foundations of Data Science (from Microsoft Research Lab)
- Free Textbook: Probability Course, Harvard University (Based on R)
- Free Book: Introduction to Statistics
- The Browser of a Data Scientist

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