Summaries of Abhishek Thakur Videos 📚

Kaggle's 30 Days Of ML (Day-9): First Machine Learning Model and Validation

Bengali.AI: Handwritten Grapheme Classification Using PyTorch (Part-2)

2. PyTorch Autograd

Kaggle's 30 Days Of ML (Day-14 Part-1): Intro to XGBoost

What is deep learning?

10K Subscribers: Approaching (almost) Any Machine Learning Problem and Talk Show

Talks S2E3 (Merve Noyan): BYOB - Build Your Own Bot

AutoNLP Preview: Auto model-selection, fine-tuning and deployment of state-of-the-art NLP models

Natural Language Processing: Tokenization (Basic)

Making Transformers go brum, brum, brum 🏎 (with Lewis Tunstall)

Kaggle's 30 Days Of ML (Day-5, Part-2): Python Loops and List Comprehension

6. Dataloader in PyTorch

The FASTEST way to build CHAT UI for LLAMA-v2

Kaggle's 30 Days Of ML (Day-5, Part-1): Python Lists and Tuples

Kaggle's 30 Days Of ML (Day-8): What is a machine learning model and what is pandas all about?

Tips To Build A Good Data Science / Machine Learning Project (For Your Portfolio)

Build Your Own PyTorch Trainer!

Kaggle's 30 Days Of ML (Competition Part-7): What are public and private leaderboard?

Building a summarizer using XGen-7b: Fully open source LLM by Salesforce

I just got access to GitHub's Codespaces and it's amazing!

Kaggle's 30 Days Of ML (Day-13 Part-2): Cross-validation

Stable Diffusion XL (SDXL) DreamBooth: Easy, Fast & Free | Beginner Friendly

100% Private & Local PDF ChatBot (without langchain)

Song Popularity Prediction: EDA with Martin Henze (Part-2)

My First Neural Network using Keras

How to convert almost any PyTorch model to ONNX and serve it using flask

Unboxing and Installing NVIDIA RTX 3090: The BFGPU

Talks S2E1: DALL·E mini - Generate images from a text prompt

Kaggle's 30 Days Of ML (Day-6): Python Strings and Dictionaries

Bengali.AI: Handwritten Grapheme Classification Using PyTorch (Part-1)

Talks # 15: Shubhadeep Roychowdhury; Applying Machine Learning on Source Code

TS-3: Time series models for finance

Kaggle's 30 Days Of ML (Day-1): Getting Started With Kaggle

Kaggle's 30 Days Of ML (Day-3): Python Functions

Content Based Image Search: InstructBLIP + Sentence Transformers + FAISS

7. Linear regression model in PyTorch

BERT Model for Toxic Comment Classification (with GitHub Copilot's help)

VS Code (codeserver) on Google Colab / Kaggle / Anywhere

Kaggle's 30 Days Of ML (Day-10): Underfitting, Overfitting & Random Forests

Movie Genre Prediction

How do I start my career in Data Science?

Text Extraction From a Corpus Using BERT (AKA Question Answering)

Kaggle's 30 Days Of ML (Competition Part-3): What is Target Encoding and how does it work?

Finetune LLMs (llama, vicuna, gptneo, pythia) without any code!

BERT on Steroids: Fine-tuning BERT for a dataset using PyTorch and Google Cloud TPUs

TS-9: Hybrid methods for time series

TS-4: Sales and demand forecasting

Song Popularity Prediction EDA with Martin Henze (Heads or Tails)

Talks S2E2 (Vasudev Gupta): Understanding BigBird (Transformers for Longer Sequences)

Handling Missing Values (with Rob Mulla)

Sentencepiece Tokenizer With Offsets For T5, ALBERT, XLM-RoBERTa And Many More

Talks S2E7 (Konrad Banachewicz): Time Series Analysis - Vintage Toolkit For Modern Times

How to create GPT-powered conversational bot for any website

Deploy Any Machine Learning Or Deep Learning Model On Google Cloud Platform (App Engine)

Talks S2E4 (Lavanya Shukla): Reproducible machine learning at scale

Tips N Tricks #3: Creating a clean inference kernel/notebook on Kaggle

What is stemming and lemmatization?

Best computer vision competitions on Kaggle (for beginners)

Training Sentiment Model Using BERT and Serving it with Flask API

The EASIEST way to finetune LLAMA-v2 on local machine!

TS-6: Deep learning for time series - sequences

1. Tensors in PyTorch

Tips N Tricks # 8: Using automatic mixed precision training with PyTorch 1.6

BARK: Free Text to Speech & Voice Cloning

Detecting Skin Cancer (Melanoma) With Deep Learning

Implementing original U-Net from scratch using PyTorch

TS-10: Validation methods for time series

TS-8: Hierarchical Time Series

Run LLAMA-v2 chat locally

Tips N Tricks #4: Using joblib to speed up almost any function (example 1)

Kaggle's 30 Days Of ML (Competition Part-4): Hyperparameter tuning using Optuna

Data representations for neural networks

Ensembling, Blending & Stacking

8. Training and validation loops in PyTorch

Dockerizing the skin cancer detection web application

End-to-End: Automated Hyperparameter Tuning For Deep Neural Networks

Talks # 14: Martin Henze; Knowledge is Power: Understanding your Data through EDA and Visualisations

Kaggle's 30 Days Of ML (Day-12 Part-2): Handling Categorical Variables

Episode 3: Handling Categorical Features in Machine Learning Problems

Tips & Tricks # 7: Fast, convenient & awesome code formatting using Black

Data Science PC Configs: From Low Range to Super-High Range

Deploy Any Machine Learning (or Deep Learning) Endpoint on Google Cloud Platform In 10 minutes

How to serve any machine learning or deep learning model using FastAPI

Custom object detection in Python using YOLOv8

Kaggle's 30 Days Of ML (Competition Part-1): Cross Validation & First Submission on Kaggle

Deploy FULLY PRIVATE & FAST LLM Chatbots! (Local + Production)

Docker For Data Scientists

Episode 4: Simple and Basic Binary Classification Metrics

Talks # 16: Issam Laradji; Build Large-Scale ML Projects & Manage Thousands of Experiments

Panels # 1: What it takes to become a Quadruple Kaggle Grandmaster?

Building a recommendation system using deep learning

Episode 5: Entity Embeddings for Categorical Variables

Talks S2E5 (Luca Massaron): Hacking Bayesian Optimization

NVIDIA Broadcast App: AI-based application for streaming / broadcasting / meeting (all features)

Data Processing For Question & Answering Systems: BERT vs. RoBERTa

Basic git commands everyone should know about

Tips N Tricks #6: How to train multiple deep neural networks on TPUs simultaneously

Episode 6: Simple and Basic Evaluation Metrics For Regression

Train LLMs in just 50 lines of code!

Build a web-app to serve a deep learning model for skin cancer detection

Best NLP competitions on Kaggle (to learn from)

9. Understanding torch.nn

What Are Decision Trees And How Do They Work? (From Scratch)

Special Announcement: Approaching (almost) any machine learning problem

Kaggle's 30 Days Of ML (Competition Part-2): Feature Engineering (Categorical & Numerical Variables)

Talks S2E6 (Louise Ferbach): Deep Learning For Survival Analysis

Kaggle's 30 Days Of ML (Day-4): Python Booleans and Conditionals

How To Become A Data Scientist In 1 Year (Learn From A Real World Example)

TS-2: ARIMA and Friends

Multi-Lingual Toxic Comment Classification using BERT and TPUs with PyTorch

Kaggle Hidden Gems - The Competition (with Heads or Tails)

Kaggle's 30 Days Of ML (Day-13 Part-1): Scikit-Learn Pipelines

4. Dataset class for simple NLP problems

Kaggle's 30 Days Of ML (Competition Part-6): Model Stacking

Kaggle's 30 Days Of ML (Day-2): Say Hello to Python: variables, types and arithmetic operations

Kaggle's 30 Days Of ML (Day-7): Working with external libraries in Python (final python day)

Hyperparameter Optimization: This Tutorial Is All You Need

Kaggle's 30 Days Of ML (Day-12 Part-1): Handling Missing Values in Datasets (imputing missing value)

TS-11: Transfer learning for time series

Stable Diffusion Inpainting with Segment Anything Model (SAM)

Tips N Tricks #5: 3 Simple and Easy Ways to Cache Functions in Python

Deep learning for (almost) any text classification problem (binary, multi-class, multi-label)

Building an entity extraction model using BERT

TS-5: Automatic for the people

Subword Tokenization: Byte Pair Encoding

Build your own Stable Doodle: Sketch to Image

I got a chance to try NVIDIA A100 GPU via qblocks.cloud

TS-7: Survival analysis

Kaggle's 30 Days Of ML (Day-11): Machine Learning Model to Predict House Prices (Intro to ML Ends)

My Journey: How I Became The World's First 4x (and 3x) Grand Master On Kaggle

How to: AI Generated QR Codes (Using Python)

🤗 AutoTrain: Train state-of-the-art image classification models (no code)

Episode 1.1: Intro and building a machine learning framework

How do random forests work?

How to train a deep learning model using docker?

How to train & deploy transformer models (BERT, RoBERTa, XLNet, etc.) without writing any code!

Training BERT Language Model From Scratch On TPUs

Tips N Tricks #2: Setting up development environment for machine learning

Kaggle's 30 Days Of ML (Competition Part-5): Model Blending 101

Captcha recognition using PyTorch (Convolutional-RNN + CTC Loss)

3. The dataset class in PyTorch

1-Click LLM Deployment!

TS-1: Curve fitting is (almost) all you need

5. Dataset class for simple image / vision problems

Kaggle's 30 Days Of ML (Day-14 Part-2): What is Data Leakage?

BERT Model Architectures For Semantic Similarity