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
- Analyze Python Code in Jupyter Notebooks - Oct 28, 2021We present a new tool that integrates modern code analysis techniques with Jupyter notebooks and helps developers find bugs as they write code.
- Getting Started with PyTorch Lightning - Oct 26, 2021As a library designed for production research, PyTorch Lightning streamlines hardware support and distributed training as well, and we’ll show how easy it is to move training to a GPU toward the end.
- Introduction to AutoEncoder and Variational AutoEncoder (VAE) - Oct 22, 2021Autoencoders and their variants are interesting and powerful artificial neural networks used in unsupervised learning scenarios. Learn how autoencoders perform in their different approaches and how to implement with Keras on the instructional data set of the MNIST digits.
- Find the Best-Matching Distribution for Your Data Effortlessly - Oct 22, 2021How to find the best-matching statistical distributions for your data points — in an automated and easy way. And, then how to extend the utility further.
- Training BPE, WordPiece, and Unigram Tokenizers from Scratch using Hugging Face - Oct 21, 2021Comparing the tokens generated by SOTA tokenization algorithms using Hugging Face's tokenizers package.
Most popular (badge-winning) recent posts on Python
- Deploying Your First Machine Learning API [Silver Blog]Effortless way to develop and deploy your machine learning API using FastAPI and Deta.
- Query Your Pandas DataFrames with SQL [Gold Blog]Learn how to query your Pandas DataFrames using the standard SQL SELECT statement, seamlessly from within your Python code.
- Teaching AI to Classify Time-series Patterns with Synthetic Data [Silver Blog]How to build and train an AI model to identify various common anomaly patterns in time-series data.
- How To Build A Database Using Python [Silver Blog]Implement your database without handling the SQL using the Flask-SQLAlchemy library.
- Path to Full Stack Data Science [Gold Blog]Start your journey toward mastering all aspects of the field of Data Science with this focused list of in-depth self-learning resources. Curated with the beginner in mind, these recommendations will help you learn efficiently, and can also offer existing professionals useful highlights for review or help filling in any gaps in skills.
- How to be a Data Scientist without a STEM degree [Silver Blog]Breaking into data science as a professional does require technical skills, a well-honed knack for problem-solving, and a willingness to swim in oceans of data. Maybe you are coming in as a career change or ready to take a new learning path in life--without having previously earned an advanced degree in a STEM field. Follow these tips to find your way into this high-demand and interesting field.
- Do You Read Excel Files with Python? There is a 1000x Faster Way [Platinum Blog]In this article, I’ll show you five ways to load data in Python. Achieving a speedup of 3 orders of magnitude.
- Learning Data Science and Machine Learning: First Steps After The Roadmap [Silver Blog]Just getting into learning data science may seem as daunting as (if not more than) trying to land your first job in the field. With so many options and resources online and in traditional academia to consider, these pre-requisites and pre-work are recommended before diving deep into data science and AI/ML.
- Automate Microsoft Excel and Word Using Python [Platinum Blog]Integrate Excel with Word to generate automated reports seamlessly.
- Django’s 9 Most Common Applications [Gold Blog]Django is a Python web application framework enjoying widespread adoption in the data science community. But what else can you use Django for? Read this article for 9 use cases where you can put Django to work.
- Prefect: How to Write and Schedule Your First ETL Pipeline with Python [Gold Blog]Workflow management systems made easy — both locally and in the cloud.
- How to Query Your Pandas Dataframe [Gold Blog]A Data Scientist’s perspective on SQL-like Python functions.
- GPU-Powered Data Science (NOT Deep Learning) with RAPIDS [Gold Blog]How 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.
- 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 [Platinum 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.
- 5 Python Data Processing Tips & Code Snippets [Silver Blog]This is a small collection of Python code snippets that a beginner might find useful for data processing.
- Pandas not enough? Here are a few good alternatives to processing larger and faster data in Python [Platinum 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.