A collection of my blogs on Data Science and Machine learning.These are hosted on Medium
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- ⚙️ Automated Machine Learning
- 👓 Computer Vision
- 🗓️ Course Reviews
- 📊 Data Analysis
- 📘 Data Science Resources
- 🎨 Data Visualisation
- 🧠 Deep Learning
- 🤖 Generative AI
- 🎙️ Interviews
- 🏅 Kaggle
- 🔢 Linear Algebra
- 🤖 Machine Learning
- 💬 Natural Language Processing
- 🐼 Pandas
- 🐍 Programming & Python
- 📄 Research Papers
- ⚖️ Responsible AI
- 🛰️ Satellite Imagery Analysis
- 🗃️ SQL
- 🤔 Thought Articles on AI
- 💡 Tips & Tricks
- Miscellaneous
- Can Recommendations from LLMs be manipulated to enhance a product’s visibility?
- Visual Guides to understand the basics of Large Language Models
- Insights into Llama 2 Development: Notes on Angela Fan’s Lecture
- Don’t just take notes — turn them into articles and share them with others-An interview with Alexey Grigorev, author of the book- Machine Learning Bookcamp
- You do not become better by employing fancy techniques but by working on the fundamentals
- Publishing Is Powerful as It Serves as a Catalyst for Scope and Writing Decisions
- Writing a book on NLP is a bit like solving a complex data science project
- A Close Look at Colab’s new updates and enhancements
- A Tour of 10 Useful Github Features
- Automate your data science project structure in three easy steps
- Building a compelling Data Science Portfolio with writing
- My favorite tools for managing, organizing, and reading research papers
- Overcoming ImageNet dataset biases with PASS
- What you see is what you’ll get: Twitter’s new strategy for displaying Images on the timeline
- My favorite tools for managing, organizing, and reading research papers
- H2O AI Hybrid Cloud: Democratizing AI for every person and every organization
- Automate your Model Documentation using H2O AutoDoc
- A Deep dive into H2O’s AutoML
- Increasing the amount and diversity of data using scikit-image in Python
- Creating custom image datasets for Deep Learning projects
- Vegetation Index calculation from Satellite Imagery
- Face Detection with Python using OpenCV
- The curious case of Simpson’s Paradox
- Reducing memory usage in pandas with smaller datatypes
- 5 Real World datasets for honing your Exploratory Data Analysis skills
- Getting started with Time Series using Pandas
- Awesome JupyterLab Extensions
- Import HTML tables into Google Sheets effortlessly
- Getting Datasets for Data Analysis tasks - Useful sites for finding datasets
- Getting Datasets for Data Analysis tasks — Advanced Google Search
- 10 Simple hacks to speed up your Data Analysis in Python
- Simplifying subplots creation in Matplotlib
- Visualizing Decision Trees with Pybaobabdt
- Render Interactive plots with Matplotlib
- Increase the cuteness quotient of your charts
- Create GitHub’s style contributions plot for your Time Series data
- A better way to visualize Decision Trees with the dtreeviz library
- Get Interactive plots directly with pandas
- Cluster Analysis in Tableau
- Quadrant Analysis in Tableau
- Visualizing large datasets with H2O
- 10 Free tools to get started with Data Visualisation-Easily & Instantly
- 5 ‘More’ Open Source tools to get started with Data Visualisation, easily
- Advanced plots in Matplotlib - Part 1
- Advanced plots in Matplotlib — Part 2
- Recreating Gapminder in Tableau: A Humble tribute to Hans Rosling
- Simplifying subplots creation in Matplotlib
- Bridging Domains: Infusing Financial, Privacy, and Software Best Practices into ML Risk Management
- Organizational Processes for Machine Learning Risk Management
- Cultural Competencies for Machine Learning Risk Management
- Explaining models built in H2O
- How effective is Google's Bold and Responsible Approach to AI?
- Exploring the Vulnerability of Language Models to Poisoning Attacks
- Explain Your Machine Learning Model Predictions with GPU-Accelerated SHAP
- Interpretable or Accurate? Why not both?
- Shapley summary plots: the latest addition to the H2O.ai’s Explainability arsenal
- Interpretable Machine Learning
- From the game of Go to Kaggle: The story of a Kaggle Grandmaster from Taiwan
- What does it take to win a Kaggle competition? Let’s hear it from the winner himself
- What it takes to become a World No 1 on Kaggle
- Meet the Data Scientist who just cannot stop winning on Kaggle
- The inspiring journey of the ‘Beluga’ of Kaggle World 🐋
- Learning from others is imperative to success on Kaggle says this Turkish GrandMaster
- Getting ‘More’ out of your Kaggle Notebooks
- How a passion for numbers turned this Mechanical Engineer into a Kaggle Grandmaster
- Geek Girls Rising: Myth or Reality
- Meet Yauhen: The first and the only Kaggle Grandmaster from Belarus
- The Data Scientist who rules the ‘Data Science for Good’ competitions on Kaggle
- From Academia to Kaggle: How a Physicist found love in Data Science
- A Data Scientist’s journey from Sudoku to Kaggle
- From clipboard to DataFrame with Pandas
- Get Interactive plots directly with Pandas
- There is more to ‘pandas.read_csv()’ than meets the eye
- A hands-on guide to ‘sorting’ dataframes in Pandas
- Reducing memory usage in pandas with smaller datatypes
- Loading large datasets in Pandas
- Extracting information from XML files into a Pandas dataframe
- PandasGUI: Analyzing Pandas dataframes with a Graphical User Interface
- Beware of the Dummy variable trap in pandas
- Pandas Plot: Deep Dive Into Plotting Directly with Pandas
- Diving Deeper into Stock Data Analysis with Python in Excel
- Five wonderful uses of ‘f- Strings’ in Python
- Use Colab more efficiently with these hacks
- Enabling notifications in your Jupyter notebooks for cell completion
- Using Python’s datatable library seamlessly on Kaggle
- Basics of BASH for Beginners
- Useful pip commands for Data Science
- Getting more value from the Pandas’ value_counts()
- Speed up your Data Analysis with Python’s Datatable package
- Useful String Methods in Python
- Elements of Functional Programming in Python
- An Overview of Python’s Datatable package
- Python’s Collections Module — High-performance container data types
- Reviewing the TensorFlow Decision Forests library
- Tensors are all you need
- Five Open-Source Machine learning libraries worth checking out
- Understanding Decision Trees
- Alternative Python libraries for Data Science
- Demystifying Neural Networks: A Mathematical Approach (Part 1)
- Demystifying Neural Networks: A Mathematical Approach (Part 2)
- Analysis of Emotion Data: A Dataset for Emotion Recognition Tasks
- Building a Simple Chatbot from Scratch in Python (using NLTK)
- Simplifying Sentiment Analysis using VADER in Python (on Social Media Text)
- Free hands-on tutorials to get started in Natural Language Processing
- Effortless Fine-Tuning of Large Language Models with Open-Source H2O LLM Studio
- How to effectively employ an AI strategy in your business
- AI for Everyone: Myth or Reality?
- How effective is Google's Bold and Responsible Approach to AI?
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