avinashmyerolkar

avinashmyerolkar

Config files for my GitHub profile.

Deep-Learning-Concepts

The Deep Learning Concepts Repository is a concise and accessible collection of essential concepts in deep learning. It provides clear explanations and examples for neural networks, CNNs, RNNs, activation functions, loss functions, backpropagation, gradient descent, and overfitting/underfitting. An invaluable resource for beginners and practitioner

Image-Classifier-CNN

This project is an image classification system built using deep learning techniques. The goal is to accurately classify images into predefined categories or classes. By leveraging convolutional neural networks (CNNs) and transfer learning, I aim to achieve high accuracy and robust performance on diverse image datasets.

Movies_Recommender_Model

The Movie Recommender System is an application that suggests personalized movie recommendations to users based on their preferences and viewing history. It uses a content-based filtering techniques to generate accurate and relevant movie recommendations.

Multilabel_Classification_Using_Transformer

Natural_Language_Processing

The "Bag of Words" (BoW) is a basic and fundamental technique in Natural Language Processing (NLP) for representing text data as numerical features that can be used in machine learning models.

Products-Top-Flop-Prediction

This project aims to predict the success or failure of products based on various features and attributes. By utilizing machine learning algorithms, I strive to accurately classify products as either top performers or underperformers in the market.

SQL

Contains questions for practise

Transformers__NLP

llama3

The official Meta Llama 3 GitHub site

avinashmyerolkar/Deep-Learning-Concepts

The Deep Learning Concepts Repository is a concise and accessible collection of essential concepts in deep learning. It provides clear explanations and examples for neural networks, CNNs, RNNs, activation functions, loss functions, backpropagation, gradient descent, and overfitting/underfitting. An invaluable resource for beginners and practitioner

avinashmyerolkar/Image-Classifier-CNN

This project is an image classification system built using deep learning techniques. The goal is to accurately classify images into predefined categories or classes. By leveraging convolutional neural networks (CNNs) and transfer learning, I aim to achieve high accuracy and robust performance on diverse image datasets.

avinashmyerolkar/Movies_Recommender_Model

The Movie Recommender System is an application that suggests personalized movie recommendations to users based on their preferences and viewing history. It uses a content-based filtering techniques to generate accurate and relevant movie recommendations.

avinashmyerolkar/Multilabel_Classification_Using_Transformer

avinashmyerolkar/Products-Top-Flop-Prediction

This project aims to predict the success or failure of products based on various features and attributes. By utilizing machine learning algorithms, I strive to accurately classify products as either top performers or underperformers in the market.

avinashmyerolkar/avinashmyerolkar

Config files for my GitHub profile.

avinashmyerolkar/Natural_Language_Processing

The "Bag of Words" (BoW) is a basic and fundamental technique in Natural Language Processing (NLP) for representing text data as numerical features that can be used in machine learning models.

avinashmyerolkar/SQL

Contains questions for practise

avinashmyerolkar/Transformers__NLP