This week, we will delve into the fascinating world of computer science and programming using Scratch, a visual programming language designed for beginners. Through hands-on projects, you will grasp fundamental concepts such as variables, loops, and conditional statements, empowering you to create your own interactive applications.
1
Lec1 Deep learning computer vision
Overview of Deep Learning's Foundational Concepts and Recent Rapid Advancements.
2
Lec2 Neural networks I
Introduction of Neural Networks I,Deep Neural Networks, Activation Fuctions
3
Lec3 Neural networks II
Introduction of Neural Networks II,Universal Approximation, Convex Fuctions.
4
Lec4 Training networks I
Training Neural Networks I: Activation Fuctions(Sigmoid, ReLU, tanh, ELU…), Data Preprocessing
5
Lec5 Training networks II
Training Neural Networks II: Weight Initialization(Activation Statistics, Xavier Initialization, Kaiming / MSRA Initialization, Residual Networks…), Overfits, Regularization, Regularization, Data Augmentation
6
Lec6 MIT Introduction to Deep Learning(vedio)
MIT Professor Alexander Amini makes introductions about foundations of Deep Learning. The course focuses on teaching the foundations of deep learning, emphasizing the importance of understanding how neural networks are built and optimized.