Python has rapidly became a leading language for Data Science and Machine Learning. In the latest KDnuggets Poll 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
- GPU-Powered Data Science (NOT Deep Learning) with RAPIDS - Aug 2, 2021How to utilize the power of your GPU for regular data science and machine learning even if you do not do a lot of deep learning work.
- KDnuggets™ News 21:n28, Jul 28: Design patterns in machine learning; The Best NLP Course is Free - Jul 28, 2021What are the Design patterns for Machine Learning and why you should know them? For more advanced readers, how to use Kafka Connect to create an open source data pipeline for processing real-time data; The state-of-the-art NLP course is freely available; Python Data Structures Compared; Update your Machine Learning skills this summer.
- Python Data Structures Compared - Jul 27, 2021Let's take a look at 5 different Python data structures and see how they could be used to store data we might be processing in our everyday tasks, as well as the relative memory they use for storage and time they take to create and access.
- Why and how should you learn “Productive Data Science”? - Jul 26, 2021What is Productive Data Science and what are some of its components?
- Top Python Data Science Interview Questions - Jul 23, 2021Six must-know technical concepts and two types of questions to test them.
Most popular (badge-winning) recent posts on Python
- Why and how should you learn “Productive Data Science”? [Gold Blog]What is Productive Data Science and what are some of its components?
- Top 6 Data Science Online Courses in 2021 [Gold Blog]As an aspiring data scientist, it is easy to get overwhelmed by the abundance of resources available on the Internet. With these 6 online courses, you can develop yourself from a novice to experienced in less than a year, and prepare you with the skills necessary to land a job in data science.
- Pandas not enough? Here are a few good alternatives to processing larger and faster data in Python [Silver Blog]While the Pandas library remains a crucial workhorse in data processing and management for data science, some limitations exist that can impact efficiencies, especially with very large data sets. Here, a few interesting alternatives to Pandas are introduced to improve your large data handling performance.
- Managing Your Reusable Python Code as a Data Scientist [Silver Blog]Here are a few approaches that I have settled on for managing my own reusable Python code as a data scientist, presented from most to least general code use, and aimed at beginners.
- Add A New Dimension To Your Photos Using Python [Silver Blog]Read this to learn how to breathe new life into your photos with a 3D Ken Burns Effect.
- Get Interactive Plots Directly With Pandas [Silver Blog]Telling a story with data is a core function for any Data Scientist, and creating data visualizations that are simultaneously illuminating and appealing can be challenging. This tutorial reviews how to create Plotly and Bokeh plots directly through Pandas plotting syntax, which will help you convert static visualizations into interactive counterparts -- and take your analysis to the next level.
- How to Generate Automated PDF Documents with Python [Platinum Blog]Discover how to leverage automation to create dazzling PDF documents effortlessly.
- 5 Tasks To Automate With Python [Platinum Blog]Here are 5 tasks you can automate with Python, and how to do it.
- How to Make Python Code Run Incredibly Fast [Silver Blog]In this article, I have explained some tips and tricks to optimize and speed up Python code.
- Top Programming Languages and Their Uses [Gold Blog]The landscape of programming languages is rich and expanding, which can make it tricky to focus on just one or another for your career. We highlight some of the most popular languages that are modern, widely used, and come with loads of packages or libraries that will help you be more productive and efficient in your work.
- A Guide On How To Become A Data Scientist (Step By Step Approach) [Platinum Blog]Becoming a Data Scientists is an exciting path, but you cannot learn data science within one year or six months—instead, it’s a lifetime process that you have to follow with proper dedication and hard work. To guide your journey, the skills outlined here are the first you must acquire to become a data scientist.
- How to Determine if Your Machine Learning Model is Overtrained [Silver Blog]WeightWatcher is based on theoretical research (done injoint with UC Berkeley) into Why Deep Learning Works, based on our Theory of Heavy Tailed Self-Regularization (HT-SR). It uses ideas from Random Matrix Theory (RMT), Statistical Mechanics, and Strongly Correlated Systems.
- Essential Linear Algebra for Data Science and Machine Learning [Gold Blog]Linear algebra is foundational in data science and machine learning. Beginners starting out along their learning journey in data science--as well as established practitioners--must develop a strong familiarity with the essential concepts in linear algebra.
- Applying Python’s Explode Function to Pandas DataFrames [Silver Blog]Read this applied Python method to solve the issue of accessing column by date/ year using the Pandas library and functions lambda(), list(), map() & explode().
- Rebuilding My 7 Python Projects [Silver Blog]This is how I rebuilt My Python Projects: Data Science, Web Development & Android Apps.
- The Most In-Demand Skills for Data Scientists in 2021 [Platinum Blog]If you are preparing to make a career as a Data Scientist or are looking for opportunities to skill-up in your current role, this analysis of in-demand skills for 2021, based on over 15,000 Data Scientist job postings, should offer you a good idea as to which programming languages and software tools are increasing and decreasing in importance.
- Shapash: Making Machine Learning Models Understandable [Gold Blog]Establishing an expectation for trust around AI technologies may soon become one of the most important skills provided by Data Scientists. Significant research investments are underway in this area, and new tools are being developed, such as Shapash, an open-source Python library that helps Data Scientists make machine learning models more transparent and understandable.
- Top 10 Python Libraries Data Scientists should know in 2021 [Platinum Blog]So many Python libraries exist that offer powerful and efficient foundations for supporting your data science work and machine learning model development. While the list may seem overwhelming, there are certain libraries you should focus your time on, as they are some of the most commonly used today.
- The Best Machine Learning Frameworks & Extensions for Scikit-learn [Silver Blog]Learn how to use a selection of packages to extend the functionality of Scikit-learn estimators.
- Know your data much faster with the new Sweetviz Python library [Gold Blog]One of the latest exploratory data analysis libraries is a new open-source Python library called Sweetviz, for just the purposes of finding out data types, missing information, distribution of values, correlations, etc. Find out more about the library and how to use it here.
- 4 Machine Learning Concepts I Wish I Knew When I Built My First Model [Silver Blog]Diving into building your first machine learning model will be an adventure -- one in which you will learn many important lessons the hard way. However, by following these four tips, your first and subsequent models will be put on a path toward excellence.