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
- Dashboards for Interpreting & Comparing Machine Learning Models - Jun 17, 2021This article discusses using Interpret to create dashboards for machine learning models.
- KDnuggets™ News 21:n22, Jun 16: Data Scientists Extinct in 10 Years? Generate Automated PDF Documents with Python - Jun 16, 2021Data Scientists be extinct in 10 years? How to generate PDF Documents with Python; Top 10 Data Science Projects for Beginners; Five types of thinking for a high performing data scientist; and how to get interactive plots directly with Pandas.
- Get Interactive Plots Directly With Pandas - Jun 14, 2021Telling 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.
- Building a Knowledge Graph for Job Search Using BERT - Jun 14, 2021A guide on how to create knowledge graphs using NER and Relation Extraction.
- How to Generate Automated PDF Documents with Python - Jun 10, 2021Discover how to leverage automation to create dazzling PDF documents effortlessly.
Most popular (badge-winning) recent posts on Python
- How to Generate Automated PDF Documents with Python [Silver Blog]Discover how to leverage automation to create dazzling PDF documents effortlessly.
- 5 Tasks To Automate With Python [Gold Blog]Here are 5 tasks you can automate with Python, and how to do it.
- 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.
- 9 Skills You Need to Become a Data Engineer [Silver Blog]A data engineer is a fast-growing profession with amazing challenges and rewards. Which skills do you need to become a data engineer? In this post, we’ll take a look at both hard and soft skills.
- Are You Still Using Pandas to Process Big Data in 2021? Here are two better options [Platinum Blog]When its time to handle a lot of data -- so much that you are in the realm of Big Data -- what tools can you use to wrangle the data, especially in a notebook environment? Pandas doesn’t handle really Big Data very well, but two other libraries do. So, which one is better and faster?
- Data Science Learning Roadmap for 2021 [Gold Blog]Venturing into the world of Data Science is an exciting, interesting, and rewarding path to consider. There is a great deal to master, and this self-learning recommendation plan will guide you toward establishing a solid understanding of all that is foundational to data science as well as a solid portfolio to showcase your developed expertise.
- Powerful Exploratory Data Analysis in just two lines of code [Gold Blog]EDA is a fundamental early process for any Data Science investigation. Typical approaches for visualization and exploration are powerful, but can be cumbersome for getting to the heart of your data. Now, you can get to know your data much faster with only a few lines of code... and it might even be fun!
- Approaching (Almost) Any Machine Learning Problem [Silver Blog]This freely-available book is a fantastic walkthrough of practical approaches to machine learning problems.
- Essential Math for Data Science: Introduction to Matrices and the Matrix Product [Silver Blog]As vectors, matrices are data structures allowing you to organize numbers. They are square or rectangular arrays containing values organized in two dimensions: as rows and columns. You can think of them as a spreadsheet. Learn more here.
- Build Your First Data Science Application [Silver Blog]Check out these seven Python libraries to make your first data science MVP application.