Topic: Python
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
- Build An AI Application with Python in 10 Easy Steps - Mar 14, 2024Explore the fundamental steps for creating a successful AI Application with Python and other tools.
- Python Enum: How To Build Enumerations in Python - Mar 11, 2024Learn how to create and use enumerations in Python using the built-in enum module.
- How to Learn Python Basics With ChatGPT - Feb 27, 2024Your Ultimate Learning Companion.
- 8 Built-in Python Decorators to Write Elegant Code - Feb 26, 2024Developers can modify a function's behavior using decorators, without changing its source code. This provides a concise and flexible way to enhance and extend the functionality of functions.
- The Right Way to Access Dictionaries in Python - Feb 21, 2024Effectively accessing dictionaries data with Python’s get() and setdefault().
Most popular (badge-winning) recent posts on Python
- What Makes Python An Ideal Programming Language For Startups [Silver Blog]In this blog, we will discuss what makes Python so popular, its features, and why you should consider Python as a programming language for your startup.
- Three R Libraries Every Data Scientist Should Know (Even if You Use Python) [Silver Blog]Check out these powerful R libraries built by the world’s biggest tech companies.
- Write Clean Python Code Using Pipes [Platinum Blog]A short and clean approach to processing iterables.
- ORDAINED: The Python Project Template [Silver Blog]Recently I decided to take the time to better understand the Python packaging ecosystem and create a project boilerplate template as an improvement over copying a directory tree and doing find and replace.
- Introduction to AutoEncoder and Variational AutoEncoder (VAE) [Silver Blog]Autoencoders 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.
- Deploying Your First Machine Learning API [Silver Blog]Effortless way to develop and deploy your machine learning API using FastAPI and Deta.
- The 20 Python Packages You Need For Machine Learning and Data Science [Gold Blog]Do you do Python? Do you do data science and machine learning? Then, you need to do these crucial Python libraries that enable nearly all you will want to do.
- Here’s Why You Need Python Skills as a Machine Learning Engineer [Silver Blog]If you want to learn how to apply Python programming skills in the context of AI applications, the UC San Diego Extension Machine Learning Engineering Bootcamp can help. Read on to find out more about how machine learning engineers use Python, and why the language dominates today’s machine learning landscape.
- 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.
- How to Create Stunning Web Apps for your Data Science Projects [Silver Blog]Data scientists do not have to learn HTML, CSS, and JavaScript to build web pages.
- 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.
- 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.