Udemy - Deep Learning with Python and Keras 2018-12 - Downloadly

Description

Deep Learning with Python and Keras is a tutorial from the Udemy site that introduces you to deep learning and teaches you how to create different models for images and text using the Python language and the Keras library. This course is designed for beginner and intermediate level programmers and people familiar with Python and helps them learn deep learning techniques and apply them to various problems.

At the beginning of the course, you will be introduced to the basics of this science by learning deep learning apps, and you will also learn about machine learning tools and techniques. Then you learn artificial neural networks and learn how to use them in solving regression and classification problems. The tutor introduces various architectures such as recurrent neural networks, torsional neural networks and fully connected networks by explaining various theoretical and practical examples. At the end of the course you will be able to identify problems and design different neural network models by deep learning.

Courses taught in this course:

Understanding Deep Learning
Using deep learning to build predictive models
Use deep learning in various applications
Using Python and keras To build deep learning models
Solve various problems with the help of deep learning
Practicing and running the model in the cloud using GPU
Training cost estimation for large models

Deep Learning with Python and Keras Course Specifications:

english language
Duration: 9 hours 56 minutes
Number of lessons: 148
Education Level: Intermediate
Instructors: Data Weekends, Jose Portilla, Francesco Mosconi
File Format: mp4

course title

148 Lecture 09:56:50

Welcome to the course!
8 lecture 37:12

date
18 lectures 01:04:58

machine learning
22 lectures 02:04:11

deep learning introduction
17 lectures 01:16:39

gradient descent
26 Lecture 01:45:14

convolutional neural network
23 Lecture 01:20:33

cloud gpu
2 lecture 1:14

recurrent neural networks
13 lectures 45:13

improving performance
19 Lecture 01:01:41

course prerequisites

Knowledge of Python, familiarity with flow control (if/else, for loops) and Pythonic constructs (functions, classes, iterables, generators)
Using the Bash shell (or equivalent command prompt) and basic commands to copy and move files
Basic knowledge of linear algebra (what is a vector, what is a matrix, how to calculate the dot product)
Using ssh to connect to a cloud computer