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

1.Join 👉@DeepLearning_ai

2.Join 👉@ComputerScience_MachineLearning


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.

1.Join 👉@DeepLearning_ai

2.Join 👉@ComputerScience_MachineLearning

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

Springer releases 65 Machine Learning and Data Science books for free

1.Join 👉@DeepLearning_ai

2.Join 👉@ComputerScience_MachineLearning

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

YOLOv4: Optimal Speed and Accuracy of Object Detection

1.Join 👉@DeepLearning_ai

2.Join 👉@ComputerScience_MachineLearning


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

1.Join 👉@DeepLearning_ai

2.Join 👉@ComputerScience_MachineLearning


3. http://bit.ly/SpringerCS

[CVPR 2020] Learning to See Through Obstructions

1.Join 👉@DeepLearning_ai
2.Join 👉@ComputerScience_MachineLearning


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).

1.Join 👉@DeepLearning_ai

2.Join 👉@ComputerScience_MachineLearning

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

Image inpainting with OpenCV and Python

1.Join 👉@DeepLearning_ai

2.Join 👉@ComputerScience_MachineLearning


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.

1.Join 👉@DeepLearning_ai

2.Join 👉@ComputerScience_MachineLearning

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

1.Join: t.me/DeepLearning_ai

2.Join: t.me/ComputerScience_MachineLearning

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

1. t.me/DeepLearning_ai

2. t.me/ComputerScience_MachineLearning

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

The best FREE combined Computer Science curriculum

1. @DeepLearning_ai

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

1. @DeepLearning_ai

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)

1. Join: @DeepLearning_ai

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

1. Join: @DeepLearning_ai

YOLOv5 is Here: State-of-the-Art Object Detection at 140 FPS

# [Tutorial] :https://blog.roboflow.ai/how-to-train-yolov5-on-a-custom-dataset/

# [Video] : https://www.youtube.com/watch?v=MdF6x6ZmLAY&feature=youtu.be

#[Repo] : https://github.com/ultralytics/yolov5

#[Colab Notebook] : https://colab.research.google.com/drive/1gDZ2xcTOgR39tGGs-EZ6i3RTs16wmzZQ

1. Join. @DeepLearning_ai

https://blog.roboflow.ai/yolov5-is-here/