Neural Networks Explained from Scratch | Build a Spotify Song Popularity Predictor with TensorFlow

In this beginner-friendly tutorial, we build a real Neural Network from scratch using TensorFlow and a real Spotify dataset. Along the way, you'll learn not only how to write the code, but also the intuition behind every major concept. 📚 In this video you'll learn: • What is a neuron? • What are weights and how are they learned? • What is bias and why is it needed? • Activation functions (ReLU & Sigmoid) • Dense layers • Sequential models • TensorFlow vs Keras • Forward propagation • Loss functions • Optimizers (Adam) • Model training with model.fit() • Model evaluation with model.evaluate() • Making predictions with model.predict() Finally, we'll build a complete neural network that predicts Spotify song popularity using TensorFlow. This video is designed for beginners and explains every concept visually before writing the code. #MachineLearning #DeepLearning #NeuralNetworks #TensorFlow #Python #ArtificialIntelligence #datascience Resources for the project Raw spotify data - https://raw.githubusercontent.com/rfordata... Github project link - https://github.com/nakul009/spotify-skip-d...