13. Deep Learning Fundamentals : Training Neural Networks | AI Course by D’SIAR TECH

Welcome to this essential lesson in Module 4 of our Artificial Intelligence course by D’SIAR TECH! 🚀 In this video, we continue our journey through Deep Learning Fundamentals by understanding how Neural Networks are trained to make accurate predictions. We’ll break down the complete training pipeline — from forward propagation, where the model makes predictions, to backpropagation, where it learns from its mistakes by adjusting weights using gradient descent. This video simplifies complex math into intuitive explanations, so you can confidently understand and apply these concepts in your own projects. Whether you're coding neural networks from scratch or using tools like TensorFlow and PyTorch, mastering the training process is key to building intelligent systems that learn from data. 🎓 What You’ll Learn in This Video: How training works in neural networks Step-by-step breakdown of forward and backward propagation The role of loss functions, gradients, and learning rate How models update their internal parameters using gradient descent Common training challenges and how to address them 📌 Subscribe and turn on notifications 🔔 to follow the full AI course series! 👉 Visit Our Website: www.dsiar.com 👉 Enroll in Our Full Course: https://www.dsiar.com/artificial-inte... 💬 Have questions? Drop them in the comments. #DSIARTECH #ArtificialIntelligence #AICourse #IntroToAI