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
- Mastering TensorFlow Variables in 5 Easy Steps - Jan 20, 2021Learn how to use TensorFlow Variables, their differences from plain Tensor objects, and when they are preferred over these Tensor objects | Deep Learning with TensorFlow 2.x.
- Loglet Analysis: Revisiting COVID-19 Projections - Jan 20, 2021We will show that the decomposition of growth into S-shaped logistic components also known as Loglet analysis, is more accurate as it takes into account the evolution of multiple covid waves.
- Comprehensive Guide to the Normal Distribution - Jan 18, 2021Drop in for some tips on how this fundamental statistics concept can improve your data science.
- Snowflake and Saturn Cloud Partner To Bring 100x Faster Data Science to Millions of Python Users - Jan 15, 2021Snowflake the cloud data platform, is partnering, integrating products, and pursuing a joint go-to-market with Saturn Cloud to help data science teams get 100x faster results. Read more about developments and how to get started here.
- Cleaner Data Analysis with Pandas Using Pipes - Jan 15, 2021Check out this practical guide on Pandas pipes.
Most popular (badge-winning) recent posts on Python
- Best Python IDEs and Code Editors You Should Know [Gold Blog]Developing machine learning algorithms requires implementing countless libraries and integrating many supporting tools and software packages. All this magic must be written by you in yet another tool -- the IDE -- that is fundamental to all your code work and can drive your productivity. These top Python IDEs and code editors are among the best tools available for you to consider, and are reviewed with their noteworthy features.
- 15 Free Data Science, Machine Learning & Statistics eBooks for 2021 [Platinum Blog]We present a curated list of 15 free eBooks compiled in a single location to close out the year.
- Generating Beautiful Neural Network Visualizations [Gold Blog]If you are looking to easily generate visualizations of neural network architectures, PlotNeuralNet is a project you should check out.
- Monte Carlo integration in Python [Gold Blog]A famous Casino-inspired trick for data science, statistics, and all of science. How to do it in Python?
- A Rising Library Beating Pandas in Performance [Gold Blog]This article compares the performance of the well-known pandas library with pypolars, a rising DataFrame library written in Rust. See how they compare.
- R or Python? Why Not Both? [Silver Blog]Do you use both R and Python, either in different projects or in the same? Check out prython, an IDE designed to handle your needs.
- Object-Oriented Programming Explained Simply for Data Scientists [Gold Blog]Read this simple but effective guide to start using Classes in Python 3.
- TabPy: Combining Python and Tableau [Platinum Blog]This article demonstrates how to get started using Python in Tableau.
- Top Python Libraries for Deep Learning, Natural Language Processing & Computer Vision [Gold Blog]This article compiles the 30 top Python libraries for deep learning, natural language processing & computer vision, as best determined by KDnuggets staff.
- From Y=X to Building a Complete Artificial Neural Network [Gold Blog]In this tutorial, we will start with the most simple artificial neural network (ANN) and move to something much more complex. We begin by building a machine learning model with no parameters—which is Y=X.
- Learn to build an end to end data science project [Gold Blog]Appreciating the process you must work through for any Data Science project is valuable before you land your first job in this field. With a well-honed strategy, such as the one outlined in this example project, you will remain productive and consistently deliver valuable machine learning models.
- Every Complex DataFrame Manipulation, Explained & Visualized Intuitively [Silver Blog]Most Data Scientists might hail the power of Pandas for data preparation, but many may not be capable of leveraging all that power. Manipulating data frames can quickly become a complex task, so eight of these techniques within Pandas are presented with an explanation, visualization, code, and tricks to remember how to do it.
- Pandas on Steroids: End to End Data Science in Python with Dask [Gold Blog]End to end parallelized data science from reading big data to data manipulation to visualisation to machine learning.
- Top Python Libraries for Data Science, Data Visualization & Machine Learning [Platinum Blog]This article compiles the 38 top Python libraries for data science, data visualization & machine learning, as best determined by KDnuggets staff.
- Building Neural Networks with PyTorch in Google Colab [Silver Blog]Combining PyTorch and Google's cloud-based Colab notebook environment can be a good solution for building neural networks with free access to GPUs. This article demonstrates how to do just that.
- Roadmap to Natural Language Processing (NLP) [Silver Blog]Check out this introduction to some of the most common techniques and models used in Natural Language Processing (NLP).
- fastcore: An Underrated Python Library [Platinum Blog]A unique python library that extends the python programming language and provides utilities that enhance productivity.
- Free From MIT: Intro to Computational Thinking and Data Science [Gold Blog]This free course from MIT will help in your transition to thinking computationally, and ultimately solving complex data science problems.
- 10 Best Machine Learning Courses in 2020 [Gold Blog]If you are ready to take your career in machine learning to the next level, then these top 10 Machine Learning Courses covering both practical and theoretical work will help you excel.
- Data Science Minimum: 10 Essential Skills You Need to Know to Start Doing Data Science [Platinum Blog]Data science is ever-evolving, so mastering its foundational technical and soft skills will help you be successful in a career as a Data Scientist, as well as pursue advance concepts, such as deep learning and artificial intelligence.
- Geographical Plots with Python [Silver Blog]When your data includes geographical information, rich map visualizations can offer significant value for you to understand your data and for the end user when interpreting analytical results.