Udemy – Deep Learning: Convolutional Neural Networks in Python 2023-3
Udemy – Deep Learning: Convolutional Neural Networks in Python 2023-3 Downloadly IRSpace

Deep Learning: Convolutional Neural Networks in Python is the name of a training course from Udemy that teaches how to use deep learning for computer vision with the help of torsional neural networks. Torque neural networks are a type of deep neural network that is used to perform visual or speech analysis in machine learning. During this course you will learn how to combine computer vision, data science, and machine learning, and how to use Theano and TensorFlow libraries.
In this course, we’re going to take a look at the SVHN data set, which uses large color images from different angles. This is quite complex, both in terms of computation and categorization, but we’ll show you how screw-in or CNN can handle these challenges. We also talk about biology and how the twisting neural network affects the animal\’s visual sector, and we show practical solutions to deep learning problems.
Courses taught in this course:
- Familiarity with torsional neural network
- Apply a torsional neural network to the sound effects
- Execute blur and search for edges in codes
- Implement an audio effect in code
- Use of torsional neural network in image categorization
Deep Learning: Convolutional Neural Networks in Python:
- Publisher: Udemy
- Instructor: Lazy Programmer Inc.
- English language
- Duration: 13 hours and 21 minutes
- Number of lessons: 75
- Level of education: Medium
Course topics on 2024/1
Course prerequisites
- Install Python, Numpy, Scipy, Matplotlib, Screen Learn, and Theano or TensorFlow
- Learn about backpropagation from Deep Learning in Python part 1
- Learn about Theano and TensorFlow implementations of Neural Networks from Deep Learning part 2
Pictures
Sample movie
Installation guide
After Extract, view with your favorite Player.
Subtitle: English
Quality: 1080p
Changes:
Version 2022/5 compared to 2018/8 has increased the number of 20 lessons and the duration of 4 hours and 43 minutes. Also, the Quality of the course has increased from 720p to 1080p.
Version 2023/3 compared to 2022/5 has increased the number of 2 lessons and the duration of 1 hours and 13 minutes.
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Size
3.58 GB