CS230 : Deep Learning

CS230 is again a relatively new course at Stanford, starting from 2017-18 term, but not new for the real OZ "Andrew NG". Deep Learning is Everywhere and Andrew NG is Everywhere :). I completed the public version, / Deep Learning Specialization on coursera/deeplearning.ai, and here is the course:

• 1. Neural Networks and Deep Learning
• 2. Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
• 3. Structuring Machine Learning Projects
• 4. Convolutional Neural Networks
• 5. Sequence Models

Grade: Programming Assignment (25%) + Midterm (25%) + Final Project (40%) + Quizzes(8%) + Attendance (2%)

• TA Handouts | CS230 Deep Learning Resource BLOG | CS230 github

Programming Assignment

Programming Assignments are the ones in Coursera.

COURSE

Deep Learning is one of the most highly sought after skills in AI. We will help you become good at Deep Learning. In this course, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. You will work on case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing. You will master not only the theory, but also see how it is applied in industry. You will practice all these ideas in Python and in TensorFlow, which we will teach. After this course, you will likely find creative ways to apply it to your work. This class is taught in the flipped-classroom format. You will watch videos and complete in-depth programming assignments and online quizzes at home, then come to class for advanced discussions and work on projects. This class will culminate in an open-ended final project, which the teaching team will help you on.

♞ Neural Networks and Deep Learning

♞ Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization

♞ Structuring Machine Learning Projects

♞ Convolutional Neural Networks

♞ Sequence Models

Course Notes are available here - cs230.stanford.edu

Exam - Spring 2018 , Solution ; Winter 2018 , Solution

• TensorFlow | Keras | PyTorch | 3blue1brown | deeplearning awesomelist

FINAL PROJECT | Past Projects

Taking this course, I did this project called, " ".