Deep Learning with Python (Udemy)
This course aims to offer a thorough grasp of Deep Learning modules so that you may learn how to create deep neural networks by growing and enhancing the number of training layers for each network. You will first master the fundamentals of calculus before moving on to comprehend backpropagation and its application in neural network training for deep learning. Eder Santana created the course after working with Kernel Machines and Deep Learning for over five years. Throughout the course, he will teach you some of the most sophisticated Deep Learning techniques for building neural networks. This is one of the best online courses to learn Deep Learning Python.
You already know how to design an artificial neural network in Python and have a TensorFlow plug-and-play script. Neural networks are a machine learning mainstay that is always a top competitor in Kaggle competitions. This is the course for you if you want to increase your knowledge of neural networks and deep learning. Backpropagation was been covered, but there were many unsolved questions. How can you boost training speed by modifying it? This course will teach you about batch and stochastic gradient descent, two approaches that allow you to train on a small sample of data at each iteration, considerably reducing training time.
Highlights:
- An introductory course that will teach you the fundamentals of Deep Learning and Neural Networks using Python.
- Discover how to use Theano to demonstrate the primary method of seamless CPU and GPU utilization, as well as how to deploy convolutional neural networks for image processing.
- Study recurrent neural networks and develop a theory that focuses on supervised learning and fits into your product offerings such as Search, Image Recognition, and Object Processing.
- Have confidence in implementing Deep Learning in your present work as well as future research after completing the course.
Duration: 2-3 hours
Digitaldefynd Rating: 3.9 out of 5
Link to enroll: https://www.udemy.com/course/draft/780922/
