Getting into neural networks: a massive, detailed Deep Learning textbook has been released 💬

Inside you'll find everything essential about models: what transformers are, how image generation works, and much more. To reinforce the learning, there are 60 exercises in Python Notebook available on the website — link 😎

🔗 AI Agents - Build and Host LLM Apps At Scale

🔗 50+ Most Asked Interview Questions on ANN

🔗 Top 5 machine learning projects:

1. Predicting House Prices: Build a machine learning model that predicts house prices based on features such as location, size, number of bedrooms, etc. This project will help you understand regression techniques and feature engineering.

2. Image Classification: Create a model that can classify images into different categories such as cats vs. dogs, fruits, or handwritten digits. This project will introduce you to convolutional neural networks (CNNs) and image processing.

3. Sentiment Analysis: Develop a sentiment analysis model that can classify text data as positive, negative, or neutral. This project will help you learn natural language processing techniques and text classification algorithms.

4. Credit Card Fraud Detection: Build a model that can detect fraudulent credit card transactions based on transaction data. This project will help you understand anomaly detection techniques and imbalanced classification problems.

5. Recommendation System: Create a recommendation system that suggests products or movies to users based on their preferences and behavior. This project will introduce you to collaborative filtering and recommendation algorithms.

🔗 AI/ ML Roadmap

💸 10 Steps of Machine Learning

🧠 Machine Learning Algorithms

💰 Calculating GPU memory for serving LLMs

💸 Most Used Machine Learning Algorithms

💸 Use of Machine Learning in Data Analysis