This article discusses several advanced techniques that can be applied at different stages of the RAG pipeline to enhance its performance in a production setting.

Beyond the Hype - LangChain's Hidden Flaws and How to Master AI Development.

Learn how to use dependency injection to decouple dependencies from our functions, methods, or classes, making it easier to test and maintain our code.

Bridging the gap between software products and customer needs, Forward Deployed Engineers are the game-changers of enterprise software. Discover their unique role in driving success and why it's in high demand. Don't miss out!

Delve into the World of Vector Databases Fueling NLP's Transformative Journey.

Learn how the differential privacy works by simulating attack on data protected with that technique.

Learn how to measure the quality of word and sentence embeddings in natural language processing (NLP), including intrinsic and extrinsic evaluation, and their strengths and limitations.

Discover how the LIME method can help you understand the important factors behind your model's predictions in a simple, intuitive way.

Discover how the SHAP method can help you understand the important factors behind your model's predictions in a simple, intuitive way.

Unveiling the mysteries of AI decisions? Let us dive into LIME, the tool that sheds light on the black box.

We often associate eloquent speech with intelligence and knowledge. But what if I told you that this assumption is not always true?

Want to know why your AI model made that decision? ELI5 has got you covered. Let's dive into Explainable AI with ELI5.

Discover the world of distributed systems and build your own Python RPC server using Flask. Harness the power of remote procedure calls today!

Get Started with RPC - A Beginner's Guide to Building a Python RPC Server Using xmlrpc and jsonrpc.

EDA Made Easy - Discover Top-10 Python Libraries That Will Take Your Data Analysis to the Next Level! Learn the Secrets of Automated EDA!

Explore the most popular Zsh plugins from the 2000+ options on the Awesome Zsh plugins GitHub project. See which ones have the highest number of stars from the Zsh community.

This post discusses importance of visual text exploration in preprocessing for classification, covers techniques (wordcloud, Sentiment Analysis, topic modeling, data cleaning) & how to use them with popular libraries. Encourages readers to try for own projects.

The most widely used libraries for plotting in python are matplotlib, Plotly, seaborn, and bokeh. This article describes 10 other powerful plotting libraries available in Python that can be used to create high-quality plots and visualizations.

"Looking for the key to unlocking valuable datasets? Dive into the world of Kaggle, UCI, and more as we unveil the best platforms for data enthusiasts."

Unlock the power of document classification with these top Python libraries! Discover the best tools for effortless text analysis and more.

Improve your regression model's accuracy and predictability by uncovering hidden errors with these essential plots.

Explore the most popular Zsh plugins from the 1800+ options on the Awesome Zsh plugins GitHub project. See which ones have the highest number of stars from the Zsh community.

Want to create beautiful visualizations from complex data? Discover the power of T-SNE for dimensionality reduction in Python.

Statistics can be tricky, but understanding kurtosis is a must for anyone who wants to avoid making common mistakes in statistical analyses. Learn how to interpret it in this comprehensive guide.

Overview of the available tools and methods for schema validation in pandas, examplary code snippets and recommendation for when to use given tool.

Using Plotly, Bokeh and Altair for interactive visualizations in the blog posts.

Using puzzle on tracing the high profile spy as excuse to showcase Markov Chains and demonstrate usage and properties e.g. Stationary distribution

On the GitHub project Awesome Zsh plugins you can find 1700+ links to plugins, themes, and Zsh plugin managers/frameworks. The number of tools listed on that page is high and it is difficult to get orientation on which plugins gained already a good reputation from the Zsh users community. This post aims at identifying the most popular tools where popularity is measured by the number of stars that Github users added to a given plugin or tool.

Having several notebook-based projects behind you might result in a mess in the projects directory. Organize your Data Science project based on Jupyter notebooks in a way that one can navigate through it. Especially that "the one" will be most probably you in a few months time. To achieve that, keep your projects directory clean, name the project in a descriptive way and take care of the internal structure of the project.

Exploratory Data Analysis of the Kaggle's "What's cooking" competition dataset to get understanding what kind of data we are dealing with and get intuition of existing dependencies.

Python implementation of blockchain in few lines of code.

There is an exhaustive but curated list of Zsh plugins posted on GitHub project Awesome Zsh plugins. You can find there 800+ links to plugins, themes and Zsh plugin managers/frameworks. Even though it is a collection of awesome stuff the number is a bit high get orientation which plugins gained already good reputation from Zsh users community. In this post I will identify most popular plugins - those which have the highest number of stars.