Neural Networks & Deep Learning Day -13

🚀 Day 13 of My Machine Learning Journey is Live!

🎥 Just uploaded a complete tutorial on:
Neural Networks & Deep Learning

In this video, I cover:
• Biological Neurons vs Artificial Neurons
• Perceptron Model
• Weights, Bias, and Activation Functions
• Sigmoid, ReLU, Tanh, Softmax
• Multi-Layer Perceptron (MLP)
• Neural Network Architecture
• Forward Propagation
• Loss Functions
• Backpropagation
• Gradient Descent
• Optimizers (SGD, RMSProp, Adam)
• Overfitting & Regularization
• Dropout & Batch Normalization
• Training Curves
• Hyperparameter Tuning
• sklearn MLPClassifier
• TensorFlow / Keras Implementation
• CNNs, RNNs, Transformers
• Real-world AI Applications
• Interview Questions

This video explains:
✅ How Neural Networks actually learn
✅ Why Deep Learning changed the AI industry
✅ How backpropagation updates weights
✅ Why ReLU replaced Sigmoid
✅ How ChatGPT and modern AI systems work internally

Perfect for beginners learning:
Machine Learning • Deep Learning • AI • Neural Networks • TensorFlow • Keras 👨‍💻

From simple perceptrons to the foundations of ChatGPT — everything explained step by step 🚀

#MachineLearning #DeepLearning #NeuralNetworks #AI #Python #TensorFlow #Keras #ArtificialIntelligence #ML #DataScience #ChatGPT #Transformer #CNN #RNN #Coding #YouTube

source