Description
Unsupervised Deep Learning in Python is the name of the video training series in the field of data science and Python development. In this training course, you will get to know the logic of machine learning. Where you learn how to use data science with the help of Python and achieve deep learning. In this course, we have tried to prepare the most basic content for you. This means that by choosing this course, you will not waste your time in any way and you will learn the most important and basic material from the very first moment.
All the step-by-step trainings given to you in this course will eventually make you familiar with limited Boltzmann machines, deep neural networks, t-SNE and PCA. In fact, this course is considered a useful course. By watching this course carefully and thoroughly, you will gain a very comprehensive understanding of machine learning. This course is actually recommended for people who want to improve their deep learning skills.
Features of Unsupervised Deep Learning in Python course
- Understand the concept of PCA and perform advanced analyses
- Getting to know the PCA algorithm and how to use it in your work
- Understanding the theory of t-SNE and how to use it in coding
- Familiarity with PCA and t-SNE constraints
- Learn how to build an autoencoder in Theano and Tensorflow
- And…
Course details:
- Duration: 10h 26m
- English language
- Number of chapters: 14
- Number of courses: 82
- Instructor: Lazy Programmer Team
Chapters of the Unsupervised Deep Learning in Python course
Prerequisites for Unsupervised Deep Learning in Python
- Knowledge of calculus and linear algebra
- Python coding skills
- Some experience with Numpy, Theano, and Tensorflow
- Know how gradient descent is used to train machine learning models
- Install Python, Numpy, and Theano
- Some probability and statistical knowledge
- Code a feedforward neural network in Theano or Tensorflow
Pictures
Sample video
Installation guide
After extracting, watch with your favorite player.
English subtitle
Quality: 720p
download link
Password file(s): www.downloadly.ir
Size
2.14 GB
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