Udemy – Unsupervised Deep Learning in Python is the name of a video tutorial in the field of data science and Python development. In this course you will learn the logic of machine learning. Where you learn how to use Python data science and gain in-depth learning. In this course, we have tried to prepare the most basic content for you. This means that you will not waste your time by choosing this course and you will learn the most important and main things from the first moment.
All of the step-by-step tutorials in this course will eventually familiarize you with Boltzmann’s limited machines, deep neural networks, t-SNE, and PCA. In fact, this course is considered as a useful course. By watching this course carefully and completely, 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 the Unsupervised Deep Learning course in Python
- Understand the concept of PCA and perform advanced analysis
- Familiarity with PCA algorithm and how to use it in your work
- Understand t-SNE theory and how to use it in coding
- Familiarity with the types of PCA and t-SNE restrictions
- Learn how to build an automatic encoder in Theano and Tensorflow
- Duration: 10h 26m
- English language
- Number of chapters: 14
- Number of courses: 82
- Instructor: Lazy Programmer Team
Unsupervised Deep Learning in Python
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 statistics knowledge
- Code a feedforward neural network in Theano or Tensorflow
After Extract, watch with your favorite Player.