- Python Lists and List Manipulation - Nov 15, 2019.
In Python, lists store an ordered collection of items which can be of different types. This post is an overview of lists and their manipulation.
Programming, Python
- What is Machine Learning on Code? - Nov 1, 2019.
Not only can MLonCode help companies streamline their codebase and software delivery processes, but it also helps organizations better understand and manage their engineering talents.
Machine Learning, Programming, Software
10 Great Python Resources for Aspiring Data Scientists - Sep 9, 2019.
This is a collection of 10 interesting resources in the form of articles and tutorials for the aspiring data scientist new to Python, meant to provide both insight and practical instruction when starting on your journey.
Data Science, Data Scientist, Programming, Python
Object-oriented programming for data scientists: Build your ML estimator - Aug 30, 2019.
Implement some of the core OOP principles in a machine learning context by building your own Scikit-learn-like estimator, and making it better.
Data Scientist, Machine Learning, Programming, Python
- How a simple mix of object-oriented programming can sharpen your deep learning prototype - Aug 1, 2019.
By mixing simple concepts of object-oriented programming, like functionalization and class inheritance, you can add immense value to a deep learning prototyping code.
Deep Learning, Keras, Programming, Python
- Neural Code Search: How Facebook Uses Neural Networks to Help Developers Search for Code Snippets - Jul 24, 2019.
Developers are always searching for answers to questions about their code. But how do they ask the right questions? Facebook is creating new NLP neural networks to help search code repositories that may advance information retrieval algorithms.
Facebook, Information Retrieval, Natural Language Processing, Neural Networks, NLP, Programming
- How to Use Python’s datetime - Jun 17, 2019.
Python's datetime package is a convenient set of tools for working with dates and times. With just the five tricks that I’m about to show you, you can handle most of your datetime processing needs.
Programming, Python, Time Series
- PyCharm for Data Scientists - May 17, 2019.
This article is a discussion of some of PyCharm's features, and a comparison with Spyder, an another popular IDE for Python. Read on to find the benefits and drawbacks of PyCharm, and an outline of when to prefer it to Spyder and vice versa.
Data Science, Data Scientist, Programming, PyCharm, Python
Top 10 Coding Mistakes Made by Data Scientists - Apr 2, 2019.
Here is a list of 10 common mistakes that a senior data scientist — who is ranked in the top 1% on Stackoverflow for python coding and who works with a lot of (junior) data scientists — frequently sees.
Data Science, Data Scientist, Mistakes, Programming
- Deploy your PyTorch model to Production - Mar 20, 2019.
This tutorial aims to teach you how to deploy your recently trained model in PyTorch as an API using Python.
Data Science Education, Data Scientist, Deep Learning, Flask, Programming, Python, PyTorch
4 Reasons Why Your Machine Learning Code is Probably Bad - Feb 26, 2019.
Your current ML workflow probably chains together several functions executed linearly. Instead of linearly chaining functions, data science code is better written as a set of tasks with dependencies between them. That is your data science workflow should be a DAG.
Data Science, Machine Learning, Programming, Python, Workflow
- How to Setup a Python Environment for Machine Learning - Feb 18, 2019.
In this tutorial, you will learn how to set up a stable Python Machine Learning development environment. You’ll be able to get right down into the ML and never have to worry about installing packages ever again.
Machine Learning, Programming, Python
- Python Patterns: max Instead of if - Jan 10, 2019.
I often have to loop over a set of objects to find the one with the greatest score. You can use an if statement and a placeholder, but there are more elegant ways!
Programming, Python
- How Different are Conventional Programming and Machine Learning? - Dec 10, 2018.
When I heard about Machine Learning I couldn't contain the amazement. I was not able to get my mind around the fact, that unlike normal software programs - which I was accustomed to - I wouldn't even have to teach a computer the "how" in detail about all the future scenarios up front.
Machine Learning, Programming
Here are the most popular Python IDEs / Editors - Dec 7, 2018.
We report on the most popular IDE and Editors, based on our poll. Jupyter is the favorite across all regions and employment types, but there is competition for no. 2 and no. 3 spots.
IDE, Jupyter, Poll, Programming, PyCharm, Python, Visual Studio Code
What is the Best Python IDE for Data Science? - Nov 14, 2018.
Before you start learning Python, choose the IDE that suits you the best. We examine many available tools, their pros and cons, and suggest how to choose the best Python IDE for you.
Data Science, IDE, Jupyter, Programming, Python
- Get a 2–6x Speed-up on Your Data Pre-processing with Python - Oct 23, 2018.
Get a 2–6x speed-up on your pre-processing with these 3 lines of code!
Data Preprocessing, Efficiency, Programming, Python
- 5 “Clean Code” Tips That Will Dramatically Improve Your Productivity - Oct 15, 2018.
TL;DR: If it isn’t tested, it’s broken; Choose meaningful names; Classes and functions should be small and obey the Single Responsibility Principle (SRP); Catch and handle exceptions, even if you don’t think you need to; Logs, logs, logs
Efficiency, Programming
- Are Vectorized Random Number Generators Actually Useful? - Aug 28, 2018.
I reported that you can multiply the speed of common (fast) random number generators such as PCG and xorshift128+ by a factor of three or four by vectorizing them using SIMD instructions. Is this actually useful in practice?
Parallelism, Programming, Random, Randomization
Programming Best Practices For Data Science - Aug 7, 2018.
In this post, I'll go over the two mindsets most people switch between when doing programming work specifically for data science: the prototype mindset and the production mindset.
Best Practices, Data Science, Pandas, Programming, Python
Cookiecutter Data Science: How to Organize Your Data Science Project - Jul 24, 2018.
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
Data Science, Programming, Project, Python
Python Regular Expressions Cheat Sheet - Apr 19, 2018.
The tough thing about learning data is remembering all the syntax. While at Dataquest we advocate getting used to consulting the Python documentation, sometimes it's nice to have a handy reference, so we've put together this cheat sheet to help you out!
Cheat Sheet, Programming, Python, Text Analytics
Data Structures Related to Machine Learning Algorithms - Jan 30, 2018.
If you want to solve some real-world problems and design a cool product or algorithm, then having machine learning skills is not enough. You would need good working knowledge of data structures.
Pages: 1 2
Machine Learning, Mathematics, Programming, Statsbot
How To Become a 10x Data Scientist, part 1 - Sep 18, 2017.
A 10x developer is someone who is 10 times more productive than average. We adapt tips and tricks from the developer community to help you become a more proficient data scientist loved by team members and stakeholders.
Advice, Algorithmia, Data Science Team, Data Scientist, Data-Driven Business, Programming
- How Not To Program the TensorFlow Graph - May 1, 2017.
Using TensorFlow from Python is like using Python to program another computer. Being thoughtful about the graphs you construct can help you avoid confusion and costly performance problems.
Deep Learning, Programming, Python, TensorFlow
- Moving from R to Python: The Libraries You Need to Know - Feb 24, 2017.
Are you considering making a move from R to Python? Here are the libraries you need to know, how they stack up to their R contemporaries, and why you should learn them.
Jupyter, Pandas, Programming, Python, R, scikit-learn, Yhat
- Great Collection of Minimal and Clean Implementations of Machine Learning Algorithms - Jan 25, 2017.
Interested in learning machine learning algorithms by implementing them from scratch? Need a good set of examples to work from? Check out this post with links to minimal and clean implementations of various algorithms.
Algorithms, Machine Learning, Programming, Python
- Top KDnuggets tweets, Jan 04-10: Cartoon: When Self-Driving Car takes you too far; A massive collection of free programming books - Jan 11, 2017.
Also AI #DataScience #MachineLearning: Main Developments 2016, Key Trends 2017; Scikit-Learn Cheat Sheet: #Python #MachineLearning
2017 Predictions, Free ebook, Programming, scikit-learn, Self-Driving Car
- Data Science 101: How to get good at R - Nov 1, 2016.
Everybody talks about R programming, how to learn, how to be good at it. But in this article, Ari Lamstein tells us his story about why and how he started with R along with how to publish, market and monetise R projects.
Ari Lamstein, Beginners, Data Science, Monetizing, Programming, R
- What Data Scientists Can Learn From Qualitative Research - Jul 14, 2016.
Learn what data scientists can learn from qualitative researchers when it comes to analysing text, and how this relates to writing quality code.
Programming, Qualitative Analytics, Qualitative Research, Text Analytics
- R Programming: Who, Where and What - Aug 11, 2015.
The “sexiest job” has the sexiest demand, and R is one of their leading weapons. Here, we are trying to capture how these unicorns are distributed, and also where you can move if you want to have great opportunities.
India, Programming, R, Salary, USA
- Perfume, computer programming, and Harvard - Oct 8, 2014.
What is the connection between Perfume, computer programming, and Harvard education? Peter Bruce explains.
edX, Harvard, Programming, Statistics.com
- Hiring Data Scientists: What to look for? - Sep 9, 2014.
Know key characteristics of what makes up a good data scientist based upon the three authors’ consulting and research experience, having collaborated with many companies world-wide on the topics of big data and analytics.
Analytics, Big Data, Business, Data Mining, Data Scientist, Hiring, Programming, Skills, Statistics
- 9 Free Books for Learning Data Mining and Data Analysis - Apr 29, 2014.
Whether you are learning data science for the first time or refreshing your memory or catching up on latest trends, these free books will help you excel through self-study.
Alex Ivanovs, Algorithms, Analysis, Data Mining, Free ebook, Programming
