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For Android: 4.1 and up	Guide: Deep Learning for computer vision offline Guide cheats tutorial
When updated: 2020-09-18	Star Rating: 0
Name: Deep Learning for computer vision offline Guide hack for android	Extension: Apk
Author: fuzzysystemzone	File Name: com.bleeddatascience.deeplearning
Current Version: 1.0	User Rating: Everyone
Downloads: 1-3	Version: mod, apk, unlock
System: Android	Type: Education

 

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About the application:

Deep learning added a large boost to the already rapidly developing field of computer vision. With deep learning, a lot of fresh apks of computer vision techniques have been introduced and are now becoming parts of our daily lives. These contain face recognition and indexing, image stylization or machine vision in self-driving vehicles. The goal of this apk is to introduce deep learning enthusiast to computer vision, starting from basics and then turning to more modern deep learning models. Deep learning for Computer vision apk will cover both photo and video recognition, including photo classification and annotation, object recognition and photo find, different object detection techniques, motion estimation, object tracking in video, human action recognition, and finally photo stylization, editing and fresh photo generation. In course project, students will learn how to build face recognition and manipulation system to understand the internal mechanics of this technology, probably the most renown and often demonstrated in films and TV-shows example of computer vision and AI. Main Specific Subject: ✔ What is Deep Learning?. ✔ Photo Fundamentals. ✔ Photo Classification Basics. ✔ Datasets for Photo Classification. ✔ Configuring Your Development Environment ✔ Make First Photo Classifier. ✔ Parameterized Learning ✔ Optimization Ways and Regularization. ✔ Neural Network Fundamentals. ✔ Convolutional Neural Networks. ✔ Training Your First CNN . ✔ Saving and Loading Your Models ✔ LeNet: Recognizing Handwritten Digits. ✔ MiniVGGNet: Going Deeper with CNNs ✔ Learning Rate Schedulers. ✔ Spotting Underfitting and Overfitting. ✔ Checkpointing Models. ✔ Visualizing Network Architectures. ✔ Computer Vision Concepts and Practice examples ✔ Out-of-the-box CNNs for Classification. ✔ Python programming core subjects. ✔ Data Science Subjects Python Code examples. ✔ Machine Learning with Code examples.

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