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
- Spam Filter in Python: Naive Bayes from Scratch - Jul 8, 2020In this blog post, learn how to build a spam filter using Python and the multinomial Naive Bayes algorithm, with a goal of classifying messages with a greater than 80% accuracy.
- KDnuggets™ News 20:n26, Jul 8: Speed up Your Numpy and Pandas; A Layman’s Guide to Data Science; Getting Started with TensorFlow 2 - Jul 8, 2020Speed up your Numpy and Pandas with NumExpr Package; A Layman's Guide to Data Science. Part 3: Data Science Workflow; Getting Started with TensorFlow 2; Feature Engineering in SQL and Python: A Hybrid Approach; Deploy Machine Learning Pipeline on AWS Fargate
- A Complete Guide To Survival Analysis In Python, part 1 - Jul 7, 2020This three-part series covers a review with step-by-step explanations and code for how to perform statistical survival analysis used to investigate the time some event takes to occur, such as patient survival during the COVID-19 pandemic, the time to failure of engineering products, or even the time to closing a sale after an initial customer contact.
- Exploratory Data Analysis on Steroids - Jul 6, 2020This is a central aspect of Data Science, which sometimes gets overlooked. The first step of anything you do should be to know your data: understand it, get familiar with it. This concept gets even more important as you increase your data volume: imagine trying to parse through thousands or millions of registers and make sense out of them.
- Feature Engineering in SQL and Python: A Hybrid Approach - Jul 2, 2020Set up your workstation, reduce workplace clutter, maintain a clean namespace, and effortlessly keep your dataset up-to-date.
Most popular (badge-winning) recent posts on Python
- Getting Started with TensorFlow 2 [Silver Blog]Learn about the latest version of TensorFlow with this hands-on walk-through of implementing a classification problem with deep learning, how to plot it, and how to improve its results.
- Speed up your Numpy and Pandas with NumExpr Package [Gold Blog]We show how to significantly speed up your mathematical calculations in Numpy and Pandas using a small library.
- 4 Free Math Courses to do and Level up your Data Science Skills [Silver Blog]Just as there is no Data Science without data, there's no science in data without mathematics. Strengthening your foundational skills in math will level you up as a data scientist that will enable you to perform with greater expertise.
- The Most Important Fundamentals of PyTorch you Should Know [Silver Blog]PyTorch is a constantly developing deep learning framework with many exciting additions and features. We review its basic elements and show an example of building a simple Deep Neural Network (DNN) step-by-step.
- Easy Speech-to-Text with Python [Gold Blog]In this blog, I am demonstrating how to convert speech to text using Python. This can be done with the help of the “Speech Recognition” API and “PyAudio” library.
- Naïve Bayes Algorithm: Everything you need to know [Silver Blog]Naïve Bayes is a probabilistic machine learning algorithm based on the Bayes Theorem, used in a wide variety of classification tasks. In this article, we will understand the Naïve Bayes algorithm and all essential concepts so that there is no room for doubts in understanding.
- Natural Language Processing with Python: The Free eBook [Gold Blog]This free eBook is an introduction to natural language processing, and to NLTK, one of the most prevalent Python NLP libraries.
- Deep Learning for Detecting Pneumonia from X-ray Images [Silver Blog]This article covers an end to end pipeline for pneumonia detection from X-ray images.
- Model Evaluation Metrics in Machine Learning [Silver Blog]A detailed explanation of model evaluation metrics to evaluate a classification machine learning model.
- Python For Everybody: The Free eBook [Gold Blog]Get back to fundamentals with this free eBook, Python For Everybody, approaching the learning of programming from a data analysis perspective.
- Build and deploy your first machine learning web app [Gold Blog]A beginner’s guide to train and deploy machine learning pipelines in Python using PyCaret.
- Natural Language Processing Recipes: Best Practices and Examples [Gold Blog]Here is an overview of another great natural language processing resource, this time from Microsoft, which demonstrates best practices and implementation guidelines for a variety of tasks and scenarios.
- Five Cool Python Libraries for Data Science [Gold Blog]Check out these 5 cool Python libraries that the author has come across during an NLP project, and which have made their life easier.
- Coronavirus COVID-19 Genome Analysis using Biopython [Silver Blog]So in this article, we will interpret, analyze the COVID-19 DNA sequence data and try to get as many insights regarding the proteins that made it up. Later will compare COVID-19 DNA with MERS and SARS and we’ll understand the relationship among them.
- How to Do Hyperparameter Tuning on Any Python Script in 3 Easy Steps [Silver Blog]With your machine learning model in Python just working, it's time to optimize it for performance. Follow this guide to setup automated tuning using any optimization library in three steps.
- Stop Hurting Your Pandas! [Silver Blog]This 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.
- Python for data analysis… is it really that simple?!? [Silver Blog]The 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.
- 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.