This Repo has all the codes for my YouTube Channel

Author: Rohan Paul

Find me here..

• 🐦 TWITTER: https://twitter.com/rohanpaul_ai
• ​👨‍🔧​ KAGGLE: https://www.kaggle.com/paulrohan2020
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• 🤖 Substack : https://rohanpaul.substack.com/
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• 📸 INSTAGRAM: https://www.instagram.com/rohan_paul_2020/

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Natural Language Processing | NLP

• Mistral 7B FineTuning with_PEFT and QLORA

• Falcon finetuning on openassistant-guanaco

• Fine Tuning Phi 1_5 with PEFT and QLoRA

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• DeBERTa Fine Tuning for Amazon Review Dataset Pytorch

• FineTuning BERT for Multi-Class Classification on custom Dataset

• Document STRIDE when Tokenizing with HuggingFace Transformer for NLP Projects

• Fine-tuning of a PreTrained Transformer model - what really happens to the weights (parameters)

• Cerebras-GPT New Large Language Model Open Sourced with Apache 2.0 License

• Roberta-Large Named Entity Recognizition on Kaggle NLP Competition with PyTorch

• Longformer end to end with Kaggle NLP competition

• Zero Shot Multilingual Sentiment Classification with PyTorch Lightning

• Fine Tuning Transformer (BERT) for Customer Review Prediction | NLP | HuggingFace

• Understanding BERT Embeddings and Tokenization | NLP | HuggingFace

• Topic Modeling with BERTopic | arxiv-abstract dataset

• Latent Dirichlet Allocation (LDA) for Topic Modeling

• Adding a custom task-specific Layer to a HuggingFace Pretrained Model

• Fine Tuning DistilBERT for Multiclass Text Classification

• Fine Tuning BERT for Named Entity Recognition (NER)

• Text Summarization by Fine Tuning Transformer Model | NLP

• Text Summarization with Transformer - BART + T5 + Pegasus

• Debarta-v3-large model fine tuning for Kaggle Competition Feedback-Prize | NLP

• Topic Modeling with BERT and Automatic Cluster Labeling

• Decoding strategies while generating text with GPT-2

• Fake News Classification with LSTM and Tensorflow

• FinBERT Sentiment Analysis for very Long Text (more than 512 Tokens) | PART 2

• FinBERT Sentiment Analysis for very Long Text Corpus (more than 512 Tokens) | PART-1

• Cosine Similarity between sentences with Transformers HuggingFace

• Zero Shot Learning - Cross Lingual Named Entity Recognition with XLM-Roberta

• BERT from Hugging Face - Few Baseline Application | NLP

• Transformer Encoder with Scaled Dot Product from Scratch

• Fuzzy String Matching in Natural Language Processing | NLP

• Understanding Word Vectors usage with Spacy Word and Sentence Similarity

• Named Entity Recognition NER using spaCy - Extracting Subject Verb Action

• Fine-Tuning-DistilBert - Hugging Face Transformer for Poem Sentiment Prediction | NLP

• Fine Tuning BERT-Based-Uncased Hugging Face Model on Kaggle Hate Speech Dataset

• Text Analytics of Tweet Emotion - EDA with Plotly

• Sentiment analysis using TextBlob and Vader

Finance and Trading with Machine Learning and Deep Learning

• Feature-Engineering-with-Stock-Exchange-Dataset | and LGBM Model to get Most Important Features Set

• LGBM (LightGBM) Model on TimeSeries Data of Cryptocurrency Prices | Crypto with Machine Learning

• Feature Engineering for Bitcoin Time Series | Prediction with XGBoost

• Bitcoin Price Prediction with FB Prophet | Time Series with Machine Learning

• FB Prophet - Analyze How Holidays affect a Time Series Forecast | Time Series with Machine Learning

• XGBoost for Time Series | Forecast Consumption Demand with Machine-Learning

• Bitcoin Prediction - FB-Prophet outperforms ARIMAX, XGBOOST & LSTM

• 28. Bitcoin Price Prediction with LSTM (Tensorflow and Keras)- PART-2

• 25. Bitcoin Price Prediction with LSTM (Tensorflow and Keras)- PART-1

• 24. Get BitCoin and other Cryptocurrency Historic Data For Free with Python

• 23 Extract Stock Market Data with yfinance for free and Tesla Stock Prediction

Computer Vision & Deep Learning Algorithms

• DCGAN from Scratch with Tensorflow - Create Fake Images from CELEB-A Dataset

• DCGAN's Generator Function - Understand Filter Size, Input Shape

• PyTorch DCGAN Implementation from Scratch | Deep Learning

• CycleGAN Architecture and Paper Walkthrough

• PyTorch CycleGAN Paper Implementation from Scratch

• Wasserstein GAN (WGAN) Architecture Understanding

• PyTorch Wasserstein GAN (WGAN) Implementation from scratch

• PyTorch Wasserstein GAN (WGAN) with Gradient Penalty from scratch

• PyTorch ConditionalGAN (Generative Adversarial Networks) from Scratch

• PyTorch DCGAN Implementation from Scratch

• DCGAN from Scratch with Tensorflow - Create Fake Images from CELEB-A Dataset

• Run Length Encoding in Image Segmentation

• PyTorch | Inception-v4 (PreTrained) - Aerial Image Segmentation

• Mean-IoU (Intersection over Union) in Object Detection | Semantic Segmentation

• Pixel Accuracy in Image Segmentation | Object Detection

• Hausdorff Distance used in Object Detection | Semantic Segmentation

• Unet Brain-MRI-Segmentation | TensorFlow

• Dice Coefficient from Scratch

• Detectron-2 Object Detection - Apply Bounding Boxes in 2 Minutes | Deep Learning

• MNIST - 99.7% Accuracy with LeNet5 | TensorFlow

• 57. GoogLeNet / Inception v1 Paper Implementation From Scratch with PyTorch

• 56. ResNet Paper Implementation From Scratch with PyTorch

• 43. LeNet5 Implementation From Scratch in PyTorch

• 42. EfficientNet Pre-Trained with PyTorch - Covid-19 X-Ray Dataset

• 37. Deep Neural Network with PyTorch - FMNIST-Dataset

• 36. Why We Scale images for Neural Network

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PyTorch Techniques for Deep Learning

• 61. Learning Rate Scheduler | PyTorch | Implementing Custom Scheduler for CycleGAN

• 55. LeNet from Scratch - Shape Calculation @ each Layer

• 54. Quantization in PyTorch | Mixed Precision Training

• 53. Plotting Activation Functions PyTorch | Sigmoid | ReLU | Tanh

• 52. Input Shape of Tensor for PyTorch Neural-Network - Conv-Layer and-Linear-Layer

• 50. Cross Entropy Loss in PyTorch and its relation with Softmax

• 48. Get Total Number of Parameters in a PyTorch Neural Network Model

• 47. Dropout Layer in PyTorch Neural Network

• 46. Label Smoothing Cross-Entropy-Loss from Scratch with PyTorch

• 44. Control Weight Decay in a PyTorch Neural Network

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Image Processing, Image Augmentation and OpenCV

• 40. Image Augmentation with Albumentation - Kaggle TensorFlow Great Barrier Reef Dataset

• 31. Understanding Shi-Tomasi Corner Detection Algorithm with OpenCV and Python

• 30. Understanding Harris Corner Detection Algorithm with OpenCV Python

• 29. Python Image Processing - Grayscale Conversion and Brightness Increase from Scratch Python

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Computer Vision Paper Discussion

• 26 𝗣𝗮𝗽𝗲𝗿 𝗘𝘅𝗽𝗹𝗮𝗶𝗻𝗲𝗱 - 𝗘𝘆𝗲𝘀 𝗧𝗲𝗹𝗹 𝗔𝗹𝗹 - 𝗗𝗲𝘁𝗲𝗰𝘁 𝗙𝗮𝗸𝗲 𝗔𝗜 𝗴𝗲𝗻𝗲𝗿𝗮𝘁𝗲𝗱 𝗳𝗮𝗰𝗲𝘀 ( 𝗖𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝗩𝗶𝘀𝗶𝗼𝗻 / 𝗚𝗔𝗡𝘀 )

• 14. GFP GAN Paper with Python code to restore resolution of old Photos

Tensorflow

• 15 Keras Custom Layers and Fundamental Building Blocks For Training Model

• 11. Tensorflow Mixed Precision Training - CIFAR10 dataset Implementation

• 8. Tensorflow Fundamentals in 45 minutes

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Kaggle Competitions / Data Science Project

• Bidirectional LSTM for Kaggle Competition(Ventilator Pressure Prediction) | PyTorch.

• 22. Predict Transaction Value of Bank Customer - Kaggle Santander Challenge.

• 17. Kaggle - Microsoft Malware Detection-BIG 2015.

• 7. Kaggle - Gravitational Wave Detection EDA and Baseline Keras Model

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Neural Network

• 9. Chain Rule Math in Backpropagation

• 13. Neural Network Implementation From Scratch in Python

• 41. Understanding the Mathematics of Gram Matrix and Why its needed for Neural Style Transfer

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Python_Challenges

• 12. Codewars Python Solution - 6kyu - Format words into Sentence

• 10. High Precision Timestamp in Python

• 6. Find Prime Factors of a Number in Python

• 4. Useful Python Script - remove special character from files and folder names

• 2. Python - Replace string in File and Directory names recursively

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Machine Learning Algo Implementations from Scratch with pure Python

• Lasso Regression from Scratch

• Polynomial Regression From Scratch

• 21. RandomizedSearchCV From Scratch without scikit-learn

• 20. GridSearchCV from Scratch without using Sckit-Learn

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Statistics

• Linear Regression From Scratch with Pure Python

• 5. Bayes Theorem in Probability implementation - simple Data Science Interview question

• 3. Probability Density Function for Discrete and Continuous Random Variable in context of Data Science

• 1. Standard Deviation in Python, Numpy and Pandas

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