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Home Programming

Deep Learning CNN: Convolutional Neural Networks with Python

September 2, 2022
in Programming, Free Course, Tutorials
Deep Learning CNN: Convolutional Neural Networks with Python

Deep Learning CNN: Convolutional Neural Networks with Python

This Asset we are sharing with you the Deep Learning CNN: Convolutional Neural Networks with Python free download links. On our website, you will find lots of premium assets free like Free Courses, Photoshop Mockups, Lightroom Preset, Photoshop Actions, Brushes & Gradient, Videohive After Effect Templates, Fonts, Luts, Sounds, 3d models, Plugins, and much more. Psdly.com is a free graphics content provider website that helps beginner graphic designers as well as freelancers who can’t afford high-cost courses and other things.

File Name:Deep Learning CNN: Convolutional Neural Networks with Python
Content Source:https://www.udemy.com/course/deep-learning-convolutional-neural-networks-theano-tensorflow/
Genre / Category:Programming
File Size :3.9GB
Publisher:udemy
Updated and Published:September 02, 2022
Product Details

Learn about one of the most powerful Deep Learning architectures yet!

The Convolutional Neural Network (CNN) has been used to obtain state-of-the-art results in computer vision tasks such as object detection, image segmentation, and generating photo-realistic images of people and things that don’t exist in the real world!

This course will teach you the fundamentals of convolution and why it’s useful for deep learning and even NLP (natural language processing).

You will learn about modern techniques such as data augmentation and batch normalization, and build modern architectures such as VGG yourself.

This course will teach you:

  • The basics of machine learning and neurons (just a review to get you warmed up!)
  • Neural networks for classification and regression (just a review to get you warmed up!)
  • How to model image data in code
  • How to model text data for NLP (including preprocessing steps for text)
  • How to build an CNN using Tensorflow 2
  • How to use batch normalization and dropout regularization in Tensorflow 2
  • How to do image classification in Tensorflow 2
  • How to do data preprocessing for your own custom image dataset
  • How to use Embeddings in Tensorflow 2 for NLP
  • How to build a Text Classification CNN for NLP (examples: spam detection, sentiment analysis, parts-of-speech tagging, named entity recognition)

All of the materials required for this course can be downloaded and installed for FREE. We will do most of our work in Numpy, Matplotlib, and Tensorflow. I am always available to answer your questions and help you along your data science journey.

This course focuses on “how to build and understand“, not just “how to use”. Anyone can learn to use an API in 15 minutes after reading some documentation. It’s not about “remembering facts”, it’s about “seeing for yourself” via experimentation. It will teach you how to visualize what’s happening in the model internally. If you want more than just a superficial look at machine learning models, this course is for you

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DOWNLOAD LINK: Deep Learning CNN: Convolutional Neural Networks with Python

Deep_Learning_CNN_Convolutional_Neural_Networks_with_Python.part1.rar – 2.0 GB
Deep_Learning_CNN_Convolutional_Neural_Networks_with_Python.part2.rar – 1.9 GB

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