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- Feature Engineering
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- Data Science Portfolio
| Title | Article | Repository | Video |
|---|---|---|---|
| Introduction to Hydra.cc: A Powerful Framework to Configure your Data Science Projects | 🔗 | 🔗 | 🔗 |
| Introduction to Weight & Biases: Track and Visualize your Machine Learning Experiments in 3 Lines of Code | 🔗 | 🔗 | |
| Kedro — A Python Framework for Reproducible Data Science Project | 🔗 | 🔗 | |
| Orchestrate a Data Science Project in Python With Prefect | 🔗 | 🔗 | |
| Orchestrate Your Data Science Project with Prefect 2.0 | 🔗 | 🔗 | 🔗 |
| DagsHub: a GitHub Supplement for Data Scientists and ML Engineers | 🔗 | 🔗 | |
| 4 pre-commit Plugins to Automate Code Reviewing and Formatting in Python | 🔗 | 🔗 | 🔗 |
| BentoML: Create an ML Powered Prediction Service in Minutes | 🔗 | 🔗 | 🔗 |
| How to Structure a Data Science Project for Readability and Transparency | 🔗 | 🔗 | |
| How to Structure an ML Project for Reproducibility and Maintainability | 🔗 | 🔗 | |
| GitHub Actions in MLOps: Automatically Check and Deploy Your ML Model | 🔗 | 🔗 | |
| Create Robust Data Pipelines with Prefect, Docker, and GitHub | 🔗 | 🔗 | |
| Create a Maintainable Data Pipeline with Prefect and DVC | 🔗 | 🔗 | |
| Build a Full-Stack ML Application With Pydantic And Prefect | 🔗 | 🔗 | 🔗 |
| DVC + GitHub Actions: Automatically Rerun Modified Components of a Pipeline | 🔗 | 🔗 | 🔗 |
| Create Observable and Reproducible Notebooks with Hex | 🔗 | 🔗 | 🔗 |
| Build Reliable Machine Learning Pipelines with Continuous Integration | 🔗 | 🔗 | 🔗 |
| Automate Machine Learning Deployment with GitHub Actions | 🔗 | 🔗 | 🔗 |
| Title | Article | Repository | Video |
|---|---|---|---|
| Introduction to DVC: Data Version Control Tool for Machine Learning Projects | 🔗 | 🔗 | 🔗 |
| Great Expectations: Always Know What to Expect From Your Data | 🔗 | 🔗 | |
| Validate Your pandas DataFrame with Pandera | 🔗 | 🔗 | 🔗 |
| Introduction to Schema: A Python Libary to Validate your Data | 🔗 | 🔗 | |
| How to Create Fake Data with Faker | 🔗 | 🔗 | |
| Hypothesis and Pandera: Generate Synthesis Pandas DataFrame for Testing | 🔗 | 🔗 | 🔗 |
| What is dbt (data build tool) and When should you use it? | 🔗 | 🔗 |
| Title | Article | Repository | Video |
|---|---|---|---|
| Pytest for Data Scientists | 🔗 | 🔗 | 🔗 |
| 4 Lessor-Known Yet Awesome Tips for Pytest | 🔗 | 🔗 | |
| DeepDiff — Recursively Find and Ignore Trivial Differences Using Python | 🔗 | 🔗 | |
| Checklist — Behavioral Testing of NLP Models | 🔗 | 🔗 | |
| Detect Defects in a Data Pipeline Early with Validation and Notifications | 🔗 | 🔗 | 🔗 |
| Write Readable Tests for Your Machine Learning Models with Behave | 🔗 | 🔗 | 🔗 |
| Title | Article | Repository |
|---|---|---|
| 3 Tools to Track and Visualize the Execution of your Python Code | 🔗 | 🔗 |
| 2 Tools to Automatically Reload when Python Files Change | 🔗 | 🔗 |
| 3 Ways to Get Notified with Python | 🔗 | 🔗 |
| How to Create Reusable Command-Line | 🔗 | |
| How to Strip Outputs and Execute Interactive Code in a Python Script | 🔗 | 🔗 |
| Sending Slack Notifications in Python with Prefect | 🔗 | 🔗 |
| Title | Article | Repository | Video |
|---|---|---|---|
| Pydash: A Kitchen Sink of Missing Python Utilities | 🔗 | 🔗 | |
| Write Clean Python Code Using Pipes | 🔗 | 🔗 | 🔗 |
| Introducing FugueSQL — SQL for Pandas, Spark, and Dask DataFrames | 🔗 | 🔗 | |
| Fugue and DuckDB: Fast SQL Code in Python | 🔗 | 🔗 | |
| Simplify Data Science Workflows on BigQuery with Fugue and Python | 🔗 | 🔗 |
| Title | Article | Repository |
|---|---|---|
| How to Effortlessly Publish your Python Package to PyPI Using Poetry | 🔗 | 🔗 |
| Typer: Build Powerful CLIs in One Line of Code using Python | 🔗 | 🔗 |
| Title | Article | Repository |
|---|---|---|
| Cython-A Speed-Up Tool for your Python Function | 🔗 | 🔗 |
| Train your Machine Learning Model 150x Faster with cuML | 🔗 | 🔗 |
| Title | Article | Repository |
|---|---|---|
| SymPy: Symbolic Computation in Python | 🔗 | 🔗 |
| Title | Article | Repository | Video |
|---|---|---|---|
| How to Monitor And Log your Machine Learning Experiment Remotely with HyperDash | 🔗 | 🔗 | |
| How to Efficiently Fine-Tune your Machine Learning Models | 🔗 | 🔗 | |
| How to Learn Non-linear Dataset with Support Vector Machines | 🔗 | 🔗 | |
| Introduction to IBM Federated Learning: A Collaborative Approach to Train ML Models on Private Data | 🔗 | 🔗 | |
| 3 Steps to Improve your Efficiency when Hypertuning ML Models | 🔗 | ||
| human-learn: Create a Human Learning Model by Drawing | 🔗 | 🔗 | |
| Patsy: Build Powerful Features with Arbitrary Python Code | 🔗 | 🔗 | |
| SHAP: Explain Any Machine Learning Model in Python | 🔗 | 🔗 | |
| Predict Movie Ratings with User-Based Collaborative Filtering | 🔗 | 🔗 | |
| River: Online Machine Learning in Python | 🔗 | 🔗 | 🔗 |
| Human-Learn: Rule-Based Learning as an Alternative to Machine Learning | 🔗 | 🔗 | 🔗 |
| Title | Article | Repository | Video |
|---|---|---|---|
| Sentiment Analysis of LinkedIn Messages | 🔗 | 🔗 | |
| Find Common Words in Article with Python Module Newspaper and NLTK | 🔗 | 🔗 | |
| How to Tokenize Tweets with Python | 🔗 | 🔗 | |
| How to Solve Analogies with Word2Vec | 🔗 | 🔗 | |
| What is PyTorch | 🔗 | 🔗 | |
| Convolutional Neural Network in Natural Language Processing | 🔗 | 🔗 | |
| Supercharge your Python String with TextBlob | 🔗 | 🔗 | 🔗 |
| pyLDAvis: Topic Modelling Exploration Tool That Every NLP Data Scientist Should Know | 🔗 | 🔗 | |
| Streamlit and spaCy: Create an App to Predict Sentiment and Word Similarities with Minimal Domain Knowledge | 🔗 | 🔗 | |
| Build a Robust Conversational Assistant with Rasa | 🔗 | 🔗 | |
| I Analyzed 2k Data Scientist and Data Engineer Jobs and This is What I Found | 🔗 | 🔗 | |
| Checklist — Behavioral Testing of NLP Models | 🔗 | 🔗 | |
| PRegEx: Write Human-Readable Regular Expressions in Python | 🔗 | 🔗 | |
| Texthero: Text Preprocessing, Representation, and Visualization for a pandas DataFrame | 🔗 | 🔗 |
| Title | Article | Repository |
|---|---|---|
| How to Create an App to Classify Dogs Using fastai and Streamlit | 🔗 | 🔗 |
| Title | Article | Repository |
|---|---|---|
| Kats: a Generalizable Framework to Analyze Time Series Data in Python | 🔗 | 🔗 |
| How to Detect Seasonality, Outliers, and Changepoints in Your Time Series | 🔗 | 🔗 |
| 4 Tools to Automatically Extract Data from Datetime in Python | 🔗 | 🔗 |
| Title | Article | Repository | Video |
|---|---|---|---|
| 3 Ways to Extract Features from Dates with Python | 🔗 | 🔗 | |
| Similarity Encoding for Dirty Categories Using dirty_cat | 🔗 | 🔗 | |
| Snorkel — A Human-In-The-Loop Platform to Build Training Data | 🔗 | 🔗 | 🔗 |
| Title | Article | Repository | Video |
|---|---|---|---|
| How to Embed Interactive Charts on your Articles and Personal Website | 🔗 | 🔗 | |
| What I Learned from Scraping 15k Data Science Articles on Medium | 🔗 | 🔗 | |
| How to Create Interactive Plots with Altair | 🔗 | 🔗 | |
| How to Create a Drop-Down Menu and a Slide Bar for your Favorite Visualization Tool | 🔗 | 🔗 | |
| I Scraped more than 1k Top Machine Learning Github Profiles and this is what I Found | 🔗 | 🔗 | |
| Top 6 Python Libraries for Visualization: Which one to Use? | 🔗 | 🔗 | |
| Introduction to Yellowbrick: A Python Library to Visualize the Prediction of your Machine Learning Model | 🔗 | 🔗 | |
| Visualize Gender-Specific Tweets with Scattertext | 🔗 | 🔗 | |
| Visualize Your Team’s Projects Using Python Gantt Chart | 🔗 | 🔗 | |
| How to Create Bindings and Conditions Between Multiple Plots Using Altair | 🔗 | 🔗 | |
| How to Sketch your Data Science Ideas With Excalidraw | 🔗 | ||
| Pyvis: Visualize Interactive Network Graphs in Python | 🔗 | 🔗 | 🔗 |
| Build and Analyze Knowledge Graphs with Diffbot | 🔗 | ||
| Observe The Friend Paradox in Facebook Data Using Python | 🔗 | 🔗 | |
| What skills and backgrounds do data scientists have in common? | 🔗 | 🔗 | |
| Visualize Similarities Between Companies With Graph Database | 🔗 | 🔗 | |
| Visualize GitHub Social Network with PyGraphistry | 🔗 | 🔗 | |
| Find the Top Bootcamps for Data Professionals From Over 5k Profiles | 🔗 | 🔗 | |
| floWeaver — Turn Flow Data Into a Sankey Diagram In Python | 🔗 | 🔗 | |
| atoti — Build a BI Platform in Python | 🔗 | 🔗 | |
| Analyze and Visualize URLs with Network Graph | 🔗 | 🔗 | |
| statsannotations: Add Statistical Significance Annotations on Seaborn Plots | 🔗 | 🔗 | 🔗 |
| Title | Article | Repository |
|---|---|---|
| How to choose stocks to invest in with Python | 🔗 | 🔗 |
| Maximize your Productivity with Python | 🔗 | 🔗 |
| How to Find a Good Match with Python | 🔗 | 🔗 |
| How to Solve a Staff Scheduling Problem with Python | 🔗 | 🔗 |
| How to Find Best Locations for your Restaurants with Python | 🔗 | 🔗 |
| How to Schedule Flights in Python | 🔗 | 🔗 |
| How to Solve a Production Planning and Inventory Problem in Python | 🔗 | 🔗 |
| Title | Article | Repository |
|---|---|---|
| Web Scrape Movie Database with Beautiful Soup | 🔗 | 🔗 |
| top-github-scraper: Scrape Top Github Users and Repositories Based On a Keyword in One Line of Code | 🔗 | 🔗 |
| Title | Article | Repository |
|---|---|---|
| Numpy Tricks for your Data Science Projects | 🔗 | 🔗 |
| Timing for Efficient Python Code | 🔗 | 🔗 |
| How to Use Lambda for Efficient Python Code | 🔗 | 🔗 |
| Python Tricks for Keeping Track of Your Data | 🔗 | 🔗 |
| Boost Your Efficiency With Specialized Dictionary Implementations in Python | 🔗 | 🔗 |
| Dictionary as an Alternative to If-Else | 🔗 | 🔗 |
| How to Use Zip to Manipulate a List of Tuples | 🔗 | 🔗 |
| Get the Most out of Your Array With These Four Numpy Methods | 🔗 | 🔗 |
| 3 Python Tricks to Read, Create, and Run Multiple Files Automatically | 🔗 | 🔗 |
| How to Exclude the Outliers in Pandas DataFrame | 🔗 | 🔗 |
| Python Clean Code: 6 Best Practices to Make Your Python Functions More Readable | 🔗 | 🔗 |
| 3 Techniques to Effortlessly Import and Execute Python Modules | 🔗 | 🔗 |
| Simplify Your Functions with Functools’ Partial and Singledispatch | 🔗 | 🔗 |
| Title | Article | Repository |
|---|---|---|
| How to Create and View Interactive Cheatsheets on the Command-line | 🔗 | |
| Understand CSV Files from your Terminal with XSV | 🔗 | |
| Prettify your Terminal Text With Termcolor and Pyfiglet | 🔗 | 🔗 |
| Stop Using Print to Debug in Python. Use Icecream Instead | 🔗 | |
| Rich: Generate Rich and Beautiful Text in the Terminal with Python | 🔗 | 🔗 |
| Create a Beautiful Dashboard in your Terminal with Wtfutil | 🔗 | 🔗 |
| 3 Tools to Monitor and Optimize your Linux System | 🔗 | |
| Ptpython: A Better Python REPL | 🔗 | 🔗 |
| fd: a Simple but Powerful Tool to Find and Execute Files on the Command Line | 🔗 | |
| Speed Up your Command-Line Navigation with These 3 Tools | 🔗 | |
| Python and Data Science Snippets on the Command Line | 🔗 | 🔗 |
| Title | Article | Repository |
|---|---|---|
| Can Datasets of a Dinosaur and a Circle have Identical Statistics? | 🔗 | 🔗 |
| Introduction to One-Way ANOVA: A Test to Compare the Means between More than Two Groups | 🔗 | 🔗 |
| Bayes’ Theorem, Clearly Explained with Visualization | 🔗 | 🔗 |
| Detect Change Points with Bayesian Inference and PyMC3 | 🔗 | 🔗 |
| Bayesian Linear Regression with Bambi | 🔗 | 🔗 |
| Earn More Salary as a Coder — Higher Degree or More Years of Experience? | 🔗 | 🔗 |
| Title | Article | Repository |
|---|---|---|
| How to Build a Matrix Module from Scratch | 🔗 | 🔗 |
| Linear Algebra for Machine Learning: Solve a System of Linear Equations | 🔗 | 🔗 |
| Title | Article | Repository |
|---|---|---|
| Convex Hull: An Innovative Approach to Gift-Wrap your Data | 🔗 | 🔗 |
| How to Visualize Social Network With Graph Theory | 🔗 | 🔗 |
| How to Search Data with KDTree | 🔗 | 🔗 |
| How to Find the Nearest Hospital with a Voronoi Diagram | 🔗 | 🔗 |
| Title | Article | Repository |
|---|---|---|
| How to Create an Interactive Startup Growth Calculator with Python | 🔗 | 🔗 |
| Streamlit and spaCy: Create an App to Predict Sentiment and Word Similarities with Minimal Domain Knowledge | 🔗 | 🔗 |
| PyWebIO: Write Interactive Web App in Script Way Using Python | 🔗 | 🔗 |
| PyWebIO 1.3.0: Add Tabs, Pin Input, and Update an Input Based on Another Input | 🔗 | 🔗 |
| Create an App to Deal with Boredom Using PyWebIO | 🔗 | 🔗 |
| Build a Robust Workflow to Visualize Trending GitHub Repositories in Python | 🔗 | 🔗 |
| Title | Article | Repository |
|---|---|---|
| Introduction to Datapane: A Python Library to Build Interactive Reports | 🔗 | |
| Datapane’s New Features: Create a Beautiful Dashboard in Python in a Few Lines of Code | 🔗 | 🔗 |
| Introduction to Datasette: Explore and Publish Your Data in One Line of Code | 🔗 | |
| How to Share your Python Objects Across Different Environments in One Line of Code | 🔗 | 🔗 |
| How to Share your Jupyter Notebook in 3 Lines of Code with Ngrok | 🔗 | |
| Introduction to Deepnote: Real-time Collaboration on Jupyter Notebook | 🔗 |
| Title | Article | Repository |
|---|---|---|
| Simulate Real-life Events in Python Using SimPy | 🔗 | 🔗 |
| How to Create Mathematical Animations like 3Blue1Brown Using Python | 🔗 | 🔗 |
| Title | Article | Repository |
|---|---|---|
| How to Learn Data Science when Life does not Give You a Break | 🔗 | |
| How to Accelerate your Data Science Career by Putting yourself in the Right Environment | 🔗 | |
| To become a Better Data Scientist, you need to Think like a Programmer | 🔗 | |
| How not to be Overwhelmed with Data Science | 🔗 |
| Title | Article | Repository |
|---|---|---|
| How to Organize your Data Science Articles with Github | 🔗 | 🔗 |
| 5 Reasons why you should Switch from Jupyter Notebook to Scripts | 🔗 | |
| 7 Reasons Why you Should Start Documenting your Code | 🔗 |
| Title | Article | Repository |
|---|---|---|
| How to Leverage Visual Studio Code for your Data Science Projects | 🔗 | |
| Top 4 Code Viewers for Data Scientist in VSCode | 🔗 | |
| Incorporate the Best Practices for Python with These Top 4 VSCode Extensions | 🔗 | |
| Boost Your Efficiency with Customized Code Snippets on VSCode | 🔗 | |
| Top 9 Keyboard Shortcuts in VSCode for Data Scientists | 🔗 |
| Title | Article | Repository |
|---|---|---|
| Python Machine Learning: A Comprehensive Handbook for Machine Learning | 🔗 |
| Title | Article | Repository |
|---|---|---|
| How to Create an Elegant Website for your Data Science Portfolio in 10 minutes | 🔗 | |
| Build an Impressive Github Profile in 3 Steps | 🔗 |
Special thanks to these supporters for supporting this project!
