Machine Learning and Data Science free online courses to do in quarantine

A. Beginner courses
1. Machine Learning
2. Machine Learning with Python

B. Intermediate courses
3. Neural Networks and Deep Learning
4. Convolutional Neural Networks

C. Advanced course
5. Advanced Machine Learning Specialization

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https://towardsdatascience.com/machine-learning-free-online-courses-from-beginner-to-advanced-f50982dce950

Awesome-Face_Recognition

papers about Face Detection; Face Alignment; Face Recognition && Face Identification && Face Verification && Face Representation; Face Reconstruction; Face Tracking; Face Super-Resolution && Face Deblurring; Face Generation && Face Synthesis; Face Transfer; Face Anti-Spoofing; Face Retrieval;

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https://github.com/ChanChiChoi/awesome-Face_Recognition#face-detection--face-segmentation

Pytorch: Step by Step implementation 3D Convolution Neural Network

Leran on how to code a PyTorch implementation of 3d CNN

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https://towardsdatascience.com/pytorch-step-by-step-implementation-3d-convolution-neural-network-8bf38c70e8b3

The TensorFlow tutorials are written as Jupyter notebooks and run directly in Google Colab—a hosted notebook environment that requires no setup.

FROM BEGINNERS TO EXPERTS
* Source Codes
* Videos
* Libraries and extensions

https://www.tensorflow.org/tutorials

Measuring distance between objects in an image with OpenCV

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https://www.pyimagesearch.com/2016/04/04/measuring-distance-between-objects-in-an-image-with-opencv/?fbclid=IwAR3DVXClBY0N8Hdv17JdIfCCyo2tdxJp8dRistQdcV7-k_99qzR7IF0AQZE

Guide how to learn and master computer vision in 2020

This post will focus on resources, which I believe will boost your knowledge in computer vision the most and mainly based on my own experience.

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https://towardsdatascience.com/guide-to-learn-computer-vision-in-2020-36f19d92c934

Springer releases 65 Machine Learning and Data Science books for free

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https://techgrabyte.com/springer-released-65-machine-learning-data-science-books-free/?fbclid=IwAR1WhzfMHZenhUaXhYZHdLAn6y5MPJXGycF_qQ7NpGjHYFfAlNhojNR7w6g

YOLOv4: Optimal Speed and Accuracy of Object Detection

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1. Paper Yolo v4: https://arxiv.org/abs/2004.10934

2. source code: https://github.com/AlexeyAB/darknet

400+ textbooks free to download

CS books on Python, deep learning, data science & AI.

You are now only searching within the Free Textbooks and Library Link special issue during Covid 19 package

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3. http://bit.ly/SpringerCS

[CVPR 2020] Learning to See Through Obstructions

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Paper:
https://arxiv.org/abs/2004.01180

Project Page:
https://www.cmlab.csie.ntu.edu.tw/~yulunliu/ObstructionRemoval

Github:
https://github.com/alex04072000/ObstructionRemoval

Deepfakes Series

Part1=>Part2=>Part3=>Part4

Finally, our last part of the series looks at detecting Deepfakes videos with machine learning (ML) and/or deep learning (DL).

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https://medium.com/@jonathan_hui/deepfakes-series-7138afb825cc

Image inpainting with OpenCV and Python

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https://www.pyimagesearch.com/2020/05/18/image-inpainting-with-opencv-and-python/

Tesseract OCR: Text localization and detection

In this tutorial, you will learn how to utilize Tesseract to detect, localize, and OCR text, all within a single, efficient function call.

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https://www.pyimagesearch.com/2020/05/25/tesseract-ocr-text-localization-and-detection/

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Paper:

https://arxiv.org/pdf/2005.12872.pdf

Github (source codes):

https://github.com/facebookresearch/detr

youtube source: (paper explained):
https://www.youtube.com/watch?v=T35ba_VXkMY

WELCOME TO PYTORCH TUTORIALS

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3 .https://pytorch.org/tutorials/

The best FREE combined Computer Science curriculum

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2. https://laconicml.com/computer-science-curriculum/

Real time face recognition with Android + TensorFlow Lite

The impressive effect of having the state-of-the-art running on your hands

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2. https://medium.com/@estebanuri/real-time-face-recognition-with-android-tensorflow-lite-14e9c6cc53a5

Effective Python: 90 Specific Ways to Write Better Python (2nd Edition) (Effective Software Development Series)

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DEEP LEARNING WITH PYTORCH

Deep Learning with PyTorch provides a detailed, hands-on introduction to building and training neural networks with PyTorch, a popular open source machine learning framework. This full book includes:

* Introduction to deep learning and the
* PyTorch library
* Pre-trained networks
* Tensors
* The mechanics of learning
* Using a neural network to fit data
* Using convolutions to generalize
* Real-world examples: Building a neural * network designed for cancer detection
* Deploying to production

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