Python leads the 11 top Data Science, Machine Learning platforms. This page brings you the latest KDnuggets Opinions and Tutorials related to Python, as well as our most popular - gold and silver-badge winning content. Enjoy!
Latest posts on Python
- Stop Hurting Your Pandas! - Apr 3, 2020This post will address the issues that can arise when Pandas slicing is used improperly. If you see the warning that reads "A value is trying to be set on a copy of a slice from a DataFrame", this post is for you.
- Free Metis Corporate Training Series: Intro to Python - Apr 2, 2020Metis Corporate Training is offering Intro to Python, a free, live online training series specially created for business professionals, and an excellent way for a team to begin their Python journey. Classes are taught live, and participants will be able to ask questions in real time. Register now.
- Python for data analysis… is it really that simple?!? - Apr 2, 2020The article addresses a simple data analytics problem, comparing a Python and Pandas solution to an R solution (using plyr, dplyr, and data.table), as well as kdb+ and BigQuery solutions. Performance improvement tricks for these solutions are then covered, as are parallel/cluster computing approaches and their limitations.
- Introduction to the K-nearest Neighbour Algorithm Using Examples - Apr 1, 2020Read this concise summary of KNN, a supervised and pattern classification learning algorithm which helps us find which class the new input belongs to when k nearest neighbours are chosen and distance is calculated between them.
- KDnuggets™ News 20:n13, Apr 1: Effective visualizations for pandemic storytelling; Machine learning for time series forecasting - Apr 1, 2020This week, read about the power of effective visualizations for pandemic storytelling; see how (not) to use machine learning for time series forecasting; learn about a deep learning breakthrough: a sub-linear deep learning algorithm that does not need a GPU?; familiarize yourself with how to painlessly analyze your time series; check out what can we learn from the latest coronavirus trends; and... KDnuggets topics?!? Also, much more.
Most popular (badge-winning) recent posts on Python
- Python and R Courses for Data Science [Silver Blog]Since Python and R are a must for today's data scientists, continuous learning is paramount. Online courses are arguably the best and most flexible way to upskill throughout ones career.
- Fourier Transformation for a Data Scientist [Gold Blog]The article contains a brief intro into Fourier transformation mathematically and its applications in AI.
- How to Optimize Your Jupyter Notebook [Gold Blog]This article walks through some simple tricks on improving your Jupyter Notebook experience, and covers useful shortcuts, adding themes, automatically generated table of contents, and more.
- 10 Python Tips and Tricks You Should Learn Today [Silver Blog]Check out this collection of 10 Python snippets that can be taken as a reference for your daily work.
- Predict Electricity Consumption Using Time Series Analysis [Silver Blog]Time series forecasting is a technique for the prediction of events through a sequence of time. In this post, we will be taking a small forecasting problem and try to solve it till the end learning time series forecasting alongside.
- Build Pipelines with Pandas Using pdpipe [Gold Blog]We show how to build intuitive and useful pipelines with Pandas DataFrame using a wonderful little library called pdpipe.
- Plotnine: Python Alternative to ggplot2 [Silver Blog]Python's plotting libraries such as matplotlib and seaborn does allow the user to create elegant graphics as well, but lack of a standardized syntax for implementing the grammar of graphics compared to the simple, readable and layering approach of ggplot2 in R makes it more difficult to implement in Python.
- 10 Free Top Notch Machine Learning Courses [Gold Blog]Are you interested in studying machine learning over the holidays? This collection of 10 free top notch courses will allow you to do just that, with something for every approach to improving your machine learning skills.
- Open Source Projects by Google, Uber and Facebook for Data Science and AI [Gold Blog]Open source is becoming the standard for sharing and improving technology. Some of the largest organizations in the world namely: Google, Facebook and Uber are open sourcing their own technologies that they use in their workflow to the public.
- Getting Started with Automated Text Summarization [Silver Blog]This article will walk through an extractive text summarization process, using a simple word frequency approach, implemented in Python.
- Automated Machine Learning Project Implementation Complexities [Silver Blog]To demonstrate the implementation complexity differences along the AutoML highway, let's have a look at how 3 specific software projects approach the implementation of just such an AutoML "solution," namely Keras Tuner, AutoKeras, and automl-gs.
- Python, Selenium & Google for Geocoding Automation: Free and Paid [Gold Blog]This tutorial will take you through two options that have automated the geocoding process for the user using Python, Selenium and Google Geocoding API.
- Data Science for Managers: Programming Languages [Silver Blog]In this article, we are going to talk about popular languages for Data Science and briefly describe each of them.
- How to Speed up Pandas by 4x with one line of code [Platinum Blog]While Pandas is the library for data processing in Python, it isn't really built for speed. Learn more about the new library, Modin, developed to distribute Pandas' computation to speedup your data prep.
- Understanding Boxplots [Silver Blog]A boxplot. It can tell you about your outliers and what their values are. It can also tell you if your data is symmetrical, how tightly your data is grouped, and if and how your data is skewed.
- Activation maps for deep learning models in a few lines of code [Silver Blog]We illustrate how to show the activation maps of various layers in a deep CNN model with just a couple of lines of code.
- The 4 Quadrants of Data Science Skills and 7 Principles for Creating a Viral Data Visualization [Silver Blog]As a data scientist, your most important skill is creating meaningful visualizations to disseminate knowledge and impact your organization or client. These seven principals will guide you toward developing charts with clarity, as exemplified with data from a recent KDnuggets poll.
- Which Data Science Skills are core and which are hot/emerging ones? [Gold Blog]We identify two main groups of Data Science skills: A: 13 core, stable skills that most respondents have and B: a group of hot, emerging skills that most do not have (yet) but want to add. See our detailed analysis.
- Explore the world of Bioinformatics with Machine Learning [Gold Blog]The article contains a brief introduction of Bioinformatics and how a machine learning classification algorithm can be used to classify the type of cancer in each patient by their gene expressions.
- Train sklearn 100x Faster [Silver Blog]As compute gets cheaper and time to market for machine learning solutions becomes more critical, we’ve explored options for speeding up model training. One of those solutions is to combine elements from Spark and scikit-learn into our own hybrid solution.
- The 5 Graph Algorithms That Data Scientists Should Know [Silver Blog]In this post, I am going to be talking about some of the most important graph algorithms you should know and how to implement them using Python.