# Your stories

Import a story
Write a story

### Docker Without the Hassle

Using repo2docker to automatically build Docker containers

Published
on Dec 17
·
4 min read
·
In Towards Data Science

### Thanks for your kind words!

Published
on Dec 15
·
1 min read

### Aaron Swartz’s story is a tragedy, especially because he was motivated by trying to make…

Have you by chance read his blog? Raw Thoughts. He clearly had wisdom beyond his years.

Published
on Dec 15
·
1 min read

### Introduction to Interactive Time Series Visualizations with Plotly in Python

Up and running with the powerful plotly visualization library

Published
on Dec 15
·
8 min read
·
In Towards Data Science

### There are plenty of people more prolific than me!

Keep a regular schedule (when I wake up and go to bed)

Published
on Dec 13
·
1 min read

### Thanks Leandro, it means a lot when I’m able to help others.

Writing can be tough, but it’s one of the most effective ways to learn new subjects. I look forward to seeing your articles and shoot me a…

Published
on Dec 13
·
1 min read

### Please Steal My Articles

A personal license for information sharing

Published
on Dec 9
·
5 min read

### How to Write a Jupyter Notebook Extension

Make the Jupyter Notebook your playground

Published
on Dec 8
·
6 min read
·
In Towards Data Science

### Jupyter Notebook Extensions

How to get the most from the notebook environment

Published
on Dec 7
·
4 min read
·
In Towards Data Science

### These API’s are really fun (and sometimes useful)!

Published
on Dec 1
·
1 min read

### Python and Slack: A Natural Match

How to send Slack messages, post plots, and monitor machine learning models programmatically with Python

Published
on Dec 1
·
7 min read
·
In Towards Data Science

### I wrote another article about deploying this to the public on AWS here.

Published
on Nov 28
·
1 min read

### Thanks! I’m glad that others find my work useful.

Published
on Nov 28
·
1 min read

### This wasn’t entirely serious, but I do think academics have a tendency to overcomplicate things.

My view is that there is nothing in data science one can’t learn on her own with an internet connection and that the biggest barrier is…

Published
on Nov 28
·
1 min read

### Estimating Probabilities with Bayesian Modeling in Python

A simple application of Probabilistic Programming with PyMC3 in Python

Published
on Nov 28
·
11 min read
·
In Towards Data Science

### Transfer Learning with Convolutional Neural Networks in PyTorch

How to use a pre-trained convolutional neural network for object recognition with PyTorch

Published
on Nov 26
·
14 min read
·
In Towards Data Science

### Deploying a Python Web App on AWS

How to share your Python project with the world

Published
on Nov 18
·
6 min read
·
In Towards Data Science

### If you run the app usingapp.run(host='0.0.0.0',

Published
on Nov 18
·
1 min read

### Deploying a Keras Deep Learning Model as a Web Application in P

Deep learning, web apps, Flask, HTML, and CSS in one project

Published
on Nov 17
·
6 min read
·
In Towards Data Science

### Modeling: Teaching a Machine Learning Algorithm to Deliver Business Value

How to train, tune, and validate a machine learning model

Published
on Nov 15
·
9 min read
·
In Towards Data Science

### Feature Engineering: What Powers Machine Learning

Extracting Features for Supervised Learning

Published
on Nov 12
·
7 min read
·
In Towards Data Science

### How to Create Value with Machine Learning

A General-Purpose Framework for Defining and Solving Meaningful Problems in 3 Steps

Published
on Nov 7
·
5 min read
·
In Towards Data Science

### Prediction Engineering: How to Set Up Your Machine Learning Problem

An explanation and implementation of the first step in solving problems with machine learning

Published
on Nov 7
·
8 min read
·
In Towards Data Science

### Recurrent Neural Networks by Example in Python

Using a Recurrent Neural Network to Write Patents

Published
on Nov 4
·
15 min read
·
In Towards Data Science

### Overcome Your Biases with Data

We’re awful at viewing the world objectively. Data can help.

Published
on Nov 1
·
6 min read
·
In Towards Data Science

### Those basic skills go a long way.

Published
on Oct 28
·
1 min read

### Great points.

Published
on Oct 28
·
1 min read

### There’s nothing wrong with getting a start in academia, there are just different standards required…

Software engineering is typically not emphasized in most beginning data science textbooks or courses, but if you make these practices into…

Published
on Oct 28
·
1 min read

### Thank you for your kind words!

Fortunately, there are lots of great resources in all these areas:

Published
on Oct 28
·
1 min read

### Great points.

The top-down approach has served me well in the past. I think a great example of it is the fast.ai series of courses for deep learning…

Published
on Oct 26
·
1 min read

### My Weaknesses as a Data Scientist

Without recognizing our weak points, we’ll never be able to overcome them

Published
on Oct 26
·
11 min read
·
In Towards Data Science

### The Power of I Don’t Know

Intellectual humility is not a weakness but a strength

Published
on Oct 17
·
8 min read

### My approach may not be best for all projects: for example, if you only need a few articles, then…

Published
on Oct 15
·
1 min read

### Yep, breaking one big problem into smaller manageable tasks is an effective method for tackling…

Published
on Oct 15
·
1 min read

### You’re absolutely right! I corrected the article and thanks for the proof-reading.

Published
on Oct 14
·
1 min read

### Your passion for writing and data science definitely show through!

Published
on Oct 14
·
1 min read

### Thank you!

Published
on Oct 14
·
1 min read

### I’m still learning these concepts myself, and writing articles helps the writer understand an idea…

Published
on Oct 14
·
1 min read

### Simpson’s Paradox: How to Prove Opposite Arguments with the Same Data

Understanding a statistical phenomenon and the importance of asking why

Published
on Oct 12
·
10 min read
·
In Towards Data Science

### Building a Recommendation System Using Neural Network Embeddings

How to use deep learning and Wikipedia to create a book recommendation system

Published
on Oct 4
·
13 min read
·
In Towards Data Science

### Thanks for sharing, I was not aware of DBPEDIA.

I am interested in what I can do with all of this data (I’ll have one application out soon), and I would enjoy hearing from the community…

Published
on Oct 3
·
1 min read

### It’s always good to have a well-laid plan!

It’s also helpful to mix learning with practicing. It sounds like you already do this by studying and then competing in Kaggle…

Published
on Oct 3
·
1 min read

### Thank you for the kind words!

Don’t feel like you have to know everything before you start contributing. We are all on this journey together, and everyone has their own…

Published
on Oct 3
·
1 min read

### Yes, one of the most common use cases for embeddings is word embeddings used for natural language…

Published
on Oct 2
·
1 min read

### Neural Network Embeddings Explained

How deep learning can represent War and Peace as a vector

Published
on Oct 1
·
8 min read
·
In Towards Data Science

### Yes, there is quite a lot of other information to be gleaned from Wikipedia.

If you are interested in exploring the talk pages of articles, then you can find those in the Wikimedia dumps as well. You can look on the…

Published
on Sep 28
·
1 min read

### Featuretools on Spark

Distributed feature engineering in Featuretools with Spark

Published
on Sep 26
·
9 min read
·
In Engineering @ Feature Labs

### Keras has more articles on Medium yet a lower weighted score for Medium.

Published
on Sep 25
·
1 min read

### Wikipedia Data Science: Working with the World’s Largest Encyclopedia

How to programmatically download and parse the Wikipedia

Published
on Sep 23
·
16 min read
·
In Towards Data Science

### Converting Medium Posts to Markdown for Your Blog

How to quickly export Medium articles to your blog

Published
on Sep 16
·
7 min read
·
In Towards Data Science

### Five Minutes to Your Own Website

How to Use GitHub Pages and Jekyll to get started with your own — entirely free — blog

Published
on Sep 16
·
5 min read
·
In Towards Data Science

### Another Machine Learning Walk-Through and a Challenge

Don’t just read about machine learning — practice it!

Published
on Sep 10
·
15 min read
·
In Towards Data Science

### Great work! I’m always glad to see another contributor to the data science community.

Published
on Sep 9
·
1 min read

### Yes, the struggle against perfection is real!

I’m glad you are able to get over the perfectionist barrier and release videos. I took a look at your YouTube channel and I’m impressed…

Published
on Sep 9
·
1 min read

### That’s a great point!

Published
on Sep 9
·
1 min read

### These are all good points to keep in mind for our daily life!

Published
on Sep 5
·
1 min read

### Practical Advice for Data Science Writing

A few useful tips to get started writing about your data science projects

Published
on Sep 3
·
10 min read
·
In Towards Data Science

### Yes, it’s very difficult to get everything perfect the first time!

This can give a false impression that data scientists know what we are doing the whole time and complete everything in one go. A more…

Published
on Aug 30
·
1 min read

### That looks correct although this competition uses the Macro average F1 Score because it’s a…

Published
on Aug 30
·
1 min read

### Thanks for sharing this resource.

Published
on Aug 30
·
1 min read

### Thanks for the kind words.

The two sources I relied on for an overview of the GBM are:

Published
on Aug 30
·
1 min read

### No problem. Although don’t thank me, thank the folks at repl.it!

Published
on Aug 30
·
1 min read

### An Implementation and Explanation of the Random Forest in Python

A guide for using and understanding the random forest by building up from a single decision tree.

Published
on Aug 30
·
15 min read
·
In Towards Data Science

### How to Put Fully Interactive, Runnable Code in a Medium Post

Code is meant to be interactive.

Published
on Aug 29
·
1 min read
·
In Towards Data Science

### A “Data Science for Good” Machine Learning Project Walk-Through in Python: Part Two

Getting the most from our model, figuring out what it all means, and experimenting with new techniques

Published
on Aug 20
·
15 min read
·
In Towards Data Science

### A “Data Science for Good“ Machine Learning Project Walk-Through in Python: Part One

Solving a complete machine learning problem for societal benefit

Published
on Aug 20
·
16 min read
·
In Towards Data Science

### Thanks for sharing your story!

Published
on Aug 19
·
1 min read

### How to Visualize a Decision Tree from a Random Forest in Python using Scikit-Learn

A helpful utility for understanding your model

Published
on Aug 18
·
2 min read
·
In Towards Data Science

### Parallelizing Feature Engineering with Dask

How to scale Featuretools using parallel processing

Published
on Aug 16
·
10 min read
·
In Towards Data Science

### While the features are not “obvious” they are all interpretable because DFS combines (stacks)…

Published
on Aug 16
·
1 min read

### Feature engineering is crucial and you’re right that if we have better features, we don’t need such…

Thanks for the resource. That’s an interesting approach to feature engineering and I’m eager to try it out!

Published
on Aug 14
·
1 min read

### One of the best parts about Featuretools is that it’s not constrained by human limits on creativity…

That’s not to say that people don’t think of great features, but only that we often miss out on some potentially useful features because we…

Published
on Aug 14
·
1 min read

### Yes, I’ve done some work on feature selection.

I see the role of the data scientist changing over the next few years as first model tuning and then feature engineering is automated. I’m…

Published
on Aug 14
·
1 min read

### I’ve used TPOT several times and while it does have functionality for feature preprocessing, such…

As far as I’m aware, Featuretools is the only open-source Python library for the kind of automated feature engineering done in these…

Published
on Aug 14
·
1 min read

### The most important part of a data science project is writing a blog post

Writing creates opportunities, gives you critical communication practice, and makes you a better data scientist through feedback

Published
on Aug 11
·
7 min read
·
In Towards Data Science

### This post doesn’t go too far into the details, but Featuretools has extensive support for…

If you take a look at this notebook, I use a number of custom time-series primitives building on functions from the tsfresh package. I’d…

Published
on Aug 9
·
1 min read

### Yes, automated feature engineering is a technique that’s only increasing in importance!

There are quite a few examples of how to use Featuretools on GitHub in addition to all the notebooks for this project. If you need any…

Published
on Aug 9
·
1 min read

### Why Automated Feature Engineering Will Change the Way You Do Machine Learning

Automated feature engineering will save you time, build better predictive models, create meaningful features, and prevent data leakage

Published
on Aug 9
·
11 min read
·
In Towards Data Science

### How to get the right data? Trying asking for it.

An example of why the most important skills in data science may not be technical

Published
on Jul 26
·
5 min read
·
In Towards Data Science

### Machine Learning Kaggle Competition: Part Three Optimization

Getting the most out of a machine learning model

Published
on Jul 20
·
15 min read
·
In Towards Data Science

### Automated Machine Learning Hyperparameter Tuning in Python

A complete walk through using Bayesian optimization for automated hyperparameter tuning in Python

Published
on Jul 3
·
17 min read
·
In Towards Data Science

### This is a must read for anyone doing any work in Pandas.

Published
on Jun 30
·
1 min read

### Thanks! I think this is a good start for feature selection, but there are still plenty of more…

Published
on Jun 28
·
1 min read

### An Introductory Example of Bayesian Optimization in Python with Hyperopt

A hands-on example for learning the foundations of a powerful optimization framework

Published
on Jun 28
·
8 min read
·
In Towards Data Science

### This is a very good point: any feature selection (or feature engineering) you do to a dataset…

Published
on Jun 26
·
1 min read

### Cross validation with a large number of folds (10+) is what I most commonly see recommended to…

Published
on Jun 26
·
1 min read

### A Conceptual Explanation of Bayesian Hyperparameter Optimization for Machine Learning

The concepts behind efficient hyperparameter tuning using Bayesian optimization

Published
on Jun 24
·
13 min read
·
In Towards Data Science

### A Feature Selection Tool for Machine Learning in Python

Using the FeatureSelector for efficient machine learning workflows

Published
on Jun 22
·
9 min read
·
In Towards Data Science

### Machine Learning Kaggle Competition Part Two: Improving

Feature engineering, feature selection, and model evaluation

Published
on Jun 19
·
20 min read
·
In Towards Data Science

### Working on it right now!

Published
on Jun 14
·
1 min read

### Python! It’s your best bet for anything data science.

Published
on Jun 14
·
1 min read

### Featuretools is very easy to use, but you’re right, it creates a significant number of features.

Published
on Jun 14
·
1 min read

### As far as I know, there aren’t any automated feature selection libraries.

I’m not sure how well featuretools scales. I know that the company behind featuretools (Feature Labs) uses this at an enterprise level, but…

Published
on Jun 10
·
1 min read

### Featuretools can be used at an enterprise level!

Also, check out the article “The AI Project Manager” for how Feature Labs used featuretools in another business application to make life…

Published
on Jun 5
·
1 min read

### Thanks for sharing.

Published
on Jun 5
·
1 min read

### Featuretools is a great library and I’m excited to use it on some more projects to avoid so much…

Published
on Jun 5
·
1 min read

### Automated Feature Engineering in Python

How to automatically create machine learning features

Published
on Jun 2
·
11 min read
·
In Towards Data Science

### You are right, Scikit-Learn no longer requires numpy arrays for training and testing.

Published
on Jun 1
·
1 min read

### This is only the first of three parts!

There are no machine learning algorithms in this article because it is only the first part, focused on data cleaning, formatting, and…

Published
on Jun 1
·
1 min read

### The Order is actually used as one of the predictor variables.

The code on GitHub is correct (the line in question is in code cell 7) but it’s intriguing that the model would think this is a helpful…

Published
on May 31
·
1 min read

### Thanks, I’m glad to help expand access to these tools!

Published
on May 29
·
1 min read

### Machine Learning Kaggle Competition Part One: Getting Started

Learning the Kaggle Environment and an Introductory Notebook

Published
on May 28
·
12 min read
·
In Towards Data Science

### I hadn’t thought about the effects of GDPR on machine learning, but since it gives parties a “right…

I know there are some other model explainer packages in R such as xgboostExplainer and breakDown (meant for any model). For Python, LIME…

Published
on May 27
·
1 min read

### If you have the time and computational resources, then you would want to try hyperparameter tuning…

There are some cool projects using automated machine learning to find the ideal model and hyperparameters given a dataset. H2O has an…

Published
on May 27
·
1 min read

### Yes, grid search results in a very large number of hyperparameter combinations.

Here is a great article detailing the effectiveness of random search.

Published
on May 27
·
1 min read

### The random search tuning gives a best result of 500 trees.

If you look at the notebook on GitHub you can see the implementation.

Published
on May 27
·
1 min read

### If you submit an issue on the GitHub repo I can try to see what is going wrong.

Published
on May 27
·
1 min read

### Thanks! Let me know if you have any problems following the code or using the Google Colab notebook.

Published
on May 24
·
1 min read

### You were right on both counts! I have fixed the mistakes in the article.

I did not enable the GPU when I was using TPOT because it does not support optimization on a GPU. (TPOT also does not test neural…

Published
on May 24
·
1 min read

### Automated Machine Learning on the Cloud in Python

An introduction to the future of data science

Published
on May 21
·
9 min read
·
In Towards Data Science

### I would try running the model with and without the variable to assess the effect on performance.

Published
on May 20
·
1 min read

### Thanks, I’m glad to hear you got something out of it!

Published
on May 20
·
1 min read

### A Complete Machine Learning Walk-Through in Python: Part Three

Interpreting a machine learning model and presenting results

Published
on May 18
·
10 min read
·
In Towards Data Science

### A Complete Machine Learning Walk-Through in Python: Part Two

Model Selection, Hyperparameter Tuning, and Evaluation

Published
on May 17
·
13 min read
·
In Towards Data Science

### A Complete Machine Learning Walk-Through in Python: Part One

Putting the machine learning pieces together

Published
on May 16
·
14 min read
·
In Towards Data Science

### I agree, regex are difficult to understand when you’re just starting out and it doesn’t help that…

Good point about the blog post being a crucial data science skill! Being able to communicate your work is nearly as important as being able…

Published
on May 16
·
1 min read

### Yes, I definitely made this project more difficult than it had to be to get a little extra practice…

The split function would have made things too easy!

Published
on May 16
·
1 min read

### Thanks for the kind words Mike!

Let me know if there are any issues accessing the notebook. Colaboratory is a really cool service but I’m still trying to get it all…

Published
on May 16
·
1 min read

### Jason, thanks for your take.

I agree stating “Your computer will fail sometime soon” is not entirely accurate, but it’s helpful to remember that computers are not…

Published
on May 2
·
1 min read

### That’s certainly a different take on things.

Published
on May 1
·
1 min read

### The analysis is conducted on the student-mat dataset! Here I read in the data from the math class:

The data is collected from a Portuguese school, so maybe that is the source of confusion?

Published
on May 1
·
1 min read

### Good question!

Published
on May 1
·
1 min read

### If your files are saved only on your laptop they might as well not exist!

How to avert computer catastrophes

Published
on Apr 30
·
3 min read
·
In Towards Data Science

### Web Scraping, Regular Expressions, and Data Visualization: Doing it all in Python

A Small Real-World Project for Learning Three Invaluable Data Science Skills

Published
on Apr 28
·
7 min read
·
In Towards Data Science

### Bayesian Linear Regression in Python: Using Machine Learning to Predict Student Grades Part 2

Implementing a Model, Interpreting Results, and Making Predictions

Published
on Apr 20
·
11 min read
·
In Towards Data Science

### Bayesian Linear Regression in Python: Using Machine Learning to Predict Student Grades Part 1

Exploratory Data Analysis, Feature Selection, and Benchmarks

Published
on Apr 20
·
11 min read
·
In Towards Data Science

### Great to hear this was helpful!

There are many great resources available online to help you out. I find I learn best by practicing techniques, and I got a lot from this…

Published
on Apr 15
·
1 min read

### Introduction to Bayesian Linear Regression

An explanation of the Bayesian approach to linear modeling

Published
on Apr 13
·
10 min read
·
In Towards Data Science

### It should be modifiable.

Published
on Apr 6
·
1 min read

### Visualizing Data with Pairs Plots in Python

How to quickly create a powerful exploratory data analysis visualization

Published
on Apr 6
·
7 min read
·
In Towards Data Science

### Data Visualization with Bokeh in Python, Part III: Making a Complete Dashboard

Creating an interactive visualization application in Bokeh

Published
on Mar 31
·
9 min read
·
In Towards Data Science

### Histograms and Density Plots in Python

Visualizing One-Dimensional Data in Python

Published
on Mar 23
·
11 min read
·
In Towards Data Science

### Data Visualization with Bokeh in Python, Part II: Interactions

Moving beyond static plots

Published
on Mar 20
·
10 min read
·
In Towards Data Science

### Data Visualization with Bokeh in Python, Part I: Getting Started

Elevate your visualization game

Published
on Mar 17
·
10 min read
·
In Towards Data Science
·
Unpublished changes

### Controlling the Web with Python

An adventure in simple web automation

Published
on Mar 10
·
9 min read
·
In Towards Data Science

### Thank you! Mohammed was entirely correct and I fixed the mistake so feel free to share.

I hope newcomers to data science find this (and all the other resources on Towards Data Science and the web) useful. The most difficult…

Published
on Mar 10
·
1 min read

### Spot on catch!

Thanks for pointing out this correction!

Published
on Mar 10
·
1 min read

### Beyond Accuracy: Precision and Recall

Choosing the right metrics for classification tasks

Published
on Mar 3
·
10 min read
·
In Towards Data Science

### Unintended Consequences and Goodhart’s Law

The importance of using the right metrics

Published
on Feb 24
·
4 min read
·
In Towards Data Science

### Data Visualization Hackathon Style

My effort to liberate data from spreadsheets

Published
on Feb 20
·
7 min read
·
In Towards Data Science

### Thanks for the clarification.

pymc3 does have a version of Hamiltonian Monte Carlo called NUTS that you can use instead of Metropolis Hastings. I’m just getting started…

Published
on Feb 14
·
1 min read

### Bayes’ Rule Applied

Using Bayesian Inference on a real-world problem

Published
on Feb 14
·
8 min read
·
In Towards Data Science

### Slow Tech: Take Back Your Mind

Technology should improve real life not replace it

Published
on Feb 11
·
2 min read

### Great advice!

Python isn’t quite the “perfect” tool for “any” problem as I put it in the title, but it can do quite a bit and doesn’t have a steep…

Published
on Feb 11
·
1 min read

### You’ll have to create a folder called ‘images’ in the same folder where you are running the script!

Published
on Feb 11
·
1 min read

### I agree my title overstated the usefulness of Python.

I don’t believe there is one “perfect tool” in programming, and I appreciate your points on the limitations of the language!

Published
on Feb 11
·
1 min read

### My title does overstate the applicability of Python, and I agree with your point.

Published
on Feb 11
·
1 min read

### Fanaticism?

Published
on Feb 11
·
1 min read

### Sorry for not explaining things well enough!

Published
on Feb 10
·
1 min read

### Markov Chain Monte Carlo in Python

A Complete Real-World Implementation

Published
on Feb 9
·
12 min read
·
In Towards Data Science

### The Misleading Effect of Noise: The Multiple Comparisons Problem

How to avoid being fooled by randomness

Published
on Feb 7
·
5 min read
·
In Towards Data Science

### I enjoy hearing about others applying these concepts!

Published
on Feb 5
·
1 min read

### Great feedback, I appreciate it!

Published
on Feb 5
·
1 min read

### You are right, the central limit theorem applies to the sample mean not the data points.

Published
on Feb 5
·
1 min read

### Great point about the sample size.

Published
on Feb 5
·
1 min read

### Nice catch!

Published
on Feb 5
·
1 min read

### Python is the Perfect Tool for any Problem

Reflecting on my first Python program

Published
on Feb 4
·
3 min read
·
In Towards Data Science

### Thank you for pointing out my mistake!

Let me know if this version of the example is better: We are testing average IQs in Florida and Washington with the null hypothesis that…

Published
on Feb 3
·
1 min read

### Statistical Significance Explained

What does it mean to prove something with data?

Published
on Feb 2
·
9 min read
·
In Towards Data Science

### If you can’t interpret a plot, that is not your problem, but the fault of whoever made the plot!

If you are having trouble interpreting a graph though, start by reading the title and labels. You need to know what physical processes the…

Published
on Jan 31
·
1 min read

### How to Master New Skills

Why trying to avoid spreadsheets is the best way to learn data science

Published
on Jan 31
·
5 min read
·
In Towards Data Science

### Great work on the blog, thanks for sharing!

I like to simplify ideas from data science because I think they are initially presented as too complex which intimidates many people. Most…

Published
on Jan 30
·
1 min read

### Any particular data science methods you would like to see explained?

Published
on Jan 30
·
1 min read

### Our education system was optimized to teach as many students as possible during the Industrial…

Published
on Jan 28
·
1 min read

### The internet hasn’t quite delivered on everything it promised us, but I do believe it has been…

Published
on Jan 28
·
1 min read

### The internet is like any other tool: it can be used for good or bad.

Published
on Jan 28
·
1 min read

### I appreciate the fact checking.

A verified quote I could find from Einstein is: “ all physical theories .. ought to lend themselves to so simple a description that even a…

Published
on Jan 28
·
1 min read

### Overfitting vs. Underfitting: A Complete Example

Exploring and solving a fundamental data science problem

Published
on Jan 28
·
10 min read
·
In Towards Data Science

### Overfitting vs. Underfitting: A Conceptual Explanation

An example-based framework of a core data science concept

Published
on Jan 27
·
6 min read
·
In Towards Data Science

### Learn By Sharing

Why I’m ditching the library to write a data science blog

Published
on Jan 24
·
4 min read
·
In Towards Data Science

### Real Life Superpowers

The three traits that turn ordinary people into modern superheroes

Published
on Jan 22
·
6 min read

### I wouldn’t consider humans’ tendency to seek patterns as a complete flaw.

For most of our history, making fast decisions and drawing conclusions unconsciously would have been a significant benefit. Now, we are…

Published
on Jan 20
·
1 min read

### All the analysis and prediction for Stocker is done using additive models with the Prophet package…

If you want to see how to use Prophet in Python for changepoint analysis, I included some work on that in Stocker which I wrote about here…

Published
on Jan 20
·
1 min read

### Correlation vs. Causation: An Example

Viewing real world statistics skeptically

Published
on Jan 19
·
5 min read
·
In Towards Data Science

### Stock Prediction in Python

Make (and lose) fake fortunes while learning real Python

Published
on Jan 19
·
12 min read
·
In Towards Data Science

### Yes, the entire project is available on GitHub.

Published
on Jan 19
·
1 min read

### The Perils of Rare Events

A review of The Black Swan: The Impact of the Highly Improbable

Published
on Jan 18
·
6 min read

### A Review of the Coursera Machine Learning Specialization

With so many high-quality options for studying machine learning, Coursera does not make the cut.

Published
on Jan 17
·
4 min read

### Stock Analysis in Python

Exploring financial data with object-oriented programming and additive models

Published
on Jan 17
·
11 min read
·
In Towards Data Science

### Matt, that is great to hear!

Let me know about your results!

Published
on Jan 15
·
1 min read

### The Failures of Common Sense

A review of Everything is Obvious: Once You Know the Answer

Published
on Jan 13
·
5 min read

### Time Series Analysis in Python: An Introduction

Additive models for time series modeling

Published
on Jan 12
·
14 min read
·
In Towards Data Science

### Hyperparameter Tuning the Random Forest in Python

Improving the Random Forest Part Two

Published
on Jan 9
·
12 min read
·
In Towards Data Science

### A Theory of Prediction

Review of The Signal and the Noise by Nate Silver

Published
on Jan 8
·
10 min read
·
In Towards Data Science

### The Simple Science of Global Warming

A five-minute primer

Published
on Jan 8
·
4 min read

### Data Science: A Personal Application

Charting the Great Weight Challenge of 2017

Published
on Jan 7
·
14 min read
·
In Towards Data Science

### Improving the Random Forest in Python Part 1

Gathering More Data and Feature Engineering

Published
on Jan 6
·
17 min read
·
In Towards Data Science

### Top Books of 2017

The 6 books that defined my year.

Published
on Jan 1
·
19 min read

### Complete Books of 2017

One year, 50 books, innumerable ideas.

Published
on Dec 29, 2017
·
9 min read

### Random Forest Simple Explanation

Understanding the Random Forest with an intuitive example

Published
on Dec 27, 2017
·
10 min read

### Random Forest in Python

A Practical End-to-End Machine Learning Example

Published
on Dec 27, 2017
·
21 min read
·
In Towards Data Science

### The Case for Criticism

When I’m wrong, call me out!

Published
on Dec 16, 2017
·
8 min read

### Artificial Intelligence Part 1: Search

Solving the Eight-Puzzle using A-Star and Local Beam Search

Published
on Sep 22, 2017
·
24 min read

### The Worst They Can Say is No

Overcoming Social Anxiety with an Attitude Change

Published
on Aug 22, 2017
·
5 min read

### Machine Learning with Python on the Enron Dataset

Investigating Fraud using Scikit-learn

Published
on Aug 20, 2017
·
31 min read

### Controlling your Location in Google Chrome

A Simple Step to Regain (some) of Your Digital Autonomy

Published
on Aug 15, 2017
·
5 min read

### Data Wrangling with Python and SQLite

Cleaning the Cleveland Open Street Map

Published
on Aug 12, 2017
·
26 min read

### Data Analysis with Python

A Brief Exploration of Baseball Statistics

Published
on Aug 12, 2017
·
29 min read

### The Technology Frontier

A review of Radical Technologies by Adam Greenfield

Published
on Aug 10, 2017
·
12 min read

### Exploratory Data Analysis with R (No Code)

Examining the Doctor’s Appointment No-Show Dataset

Published
on Aug 8, 2017
·
30 min read

### Exploratory Data Analysis with R

Examining the Doctor’s Appointment No-Show Dataset

Published
on Aug 8, 2017
·
42 min read

### Facial Recognition Using Google’s Convolutional Neural Network

Training the Inception-v3 Neural Network for a New Task

Published
on Aug 7, 2017
·
37 min read

### The Ascent of Humanity

A Review of Sapiens by Yuval Harari

Published
on Aug 1, 2017
·
17 min read

### Make an Effort, Not an Excuse

Overcoming the “I would, but…” response

Published
on Jul 30, 2017
·
7 min read

### Object Recognition with Google’s Convolutional Neural Networks

Classifying Images Using Google’s Pre-Trained Inception CNN Models

Published
on Jul 27, 2017
·
11 min read

### Deep Neural Network Classifier

A Scikit-learn compatible Deep Neural Network built with TensorFlow

Published
on Jul 25, 2017
·
14 min read

### NASA Internship Report

Near Earth Asteroid Scout Attitude Control System Validation and Verification

Published
on Jul 19, 2017
·
47 min read

### The Triumph of Peace

A review of The Better Angels of Our Nature: Why Violence Has Declined

Published
on Jul 5, 2017
·
14 min read

### Home of the Scared

A review of A Culture of Fear: Why Americans are Afraid of the Wrong Things

Published
on Jul 1, 2017
·
9 min read

### Capstone Project: Mercedes-Benz Greener Manufacturing Competition

Udacity Machine Learning Engineer Nanodegree

Published
on Jun 30, 2017
·
42 min read

### The Vanquishing of War, Plague and Famine

Part 1 of the Optimist’s Guide to the 21st Century

Published
on Jun 17, 2017
·
14 min read

### Screw the Environment, but Consider Your Wallet

When the Health of the Environment and the Health of Your Wallet Align

Published
on Jun 10, 2017
·
7 min read