Data Analytics
Practical Guide to Leveraging the Power of Algorithms, Data Science, Data Mining, Statistics, Big Data, and Predictive Analysis to Improve Business, Work, and Life
#book
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Neural Networks: A Visual Introduction for Beginners by Michael Taylor
#book
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COALESCE framework
#paper
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https://arxiv.org/pdf/2008.01936.pdf

How to Build a Custom YOLOv4 Object Detector using TensorFlow
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https://morioh.com/p/f9702a8223b2

CODE: https://github.com/theAIGuysCode/tensorflow-yolov4-tflite

Using Flask to optimize performance with Mask R-CNN segmentation(with source code)

https://medium.com/medialesson/using-flask-to-optimize-performance-with-mask-r-cnn-segmentation-39752f153029

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Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
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Top 20+ highly ranked Coursera Courses for Data Science & Machine Learning beginners and advanced
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https://nuggetsnetwork.com/blog/Top-Coursera-DataScience-Courses.html

Free course on Data Visualisation Methods
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Link : bit.ly/2XY4Suw

A Smarter Way to Learn Python: Learn it faster. Remember it longer
#book #python
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Documentation:

1) https://bigml.com/developers

2) https://predictionio.apache.org/datacollection/eventapi/

3) https://docs.anaconda.com/

4) https://github.com/blue-yonder

5) https://docs.mljar.com/

6) https://nupic.docs.numenta.org/

7) https://docs.recombee.com/

8) https://indico.io/docs/

9) https://api.animetrics.com/documentation

10) https://face.eyedea.cz:8080/api/face/docs

11) https://www.betafaceapi.com/wpa/index.php/documentation

12) https://docs.imagga.com/

13) https://wit.ai/docs

14) https://docs.api.bitext.com/

15) https://api.geneea.com/

16) https://www.diffbot.com/dev/docs/

17) https://yactraq.com/contact-trial/

18) https://monkeylearn.com/api/v3/

19) https://help.hutoma.ai/article/ym34wr87lx-hutoma-chat-api

20) https://php-nlp-tools.com/documentation/

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1. Cassie Kozyrkov : https://www.linkedin.com/in/cassie-kozyrkov-9531919/
• Medium : https://medium.com/@kozyrkov

2. Ben Taylor : https://www.linkedin.com/in/bentaylordata/

3. Dat Tran : https://www.linkedin.com/in/dat-tran-a1602320/

4. Ian Goodfellow : https://www.linkedin.com/in/ian-goodfellow-b7187213

5. Jose Marcial Portilla : https://www.linkedin.com/in/jmportilla/

6. Koo Ping Shung : https://www.linkedin.com/in/koopingshung/

7. Lex Fridman : https://www.linkedin.com/in/lexfridman/

8. Kristen Kehrer : https://www.linkedin.com/in/kristen-kehrer-datamovesme/

9. Srivatsan Srinivasan : https://www.linkedin.com/in/srivatsan-srinivasan-b8131b/

10. Andrew Ng : https://www.linkedin.com/in/andrewyng

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Introducing Opacus: A high-speed library for training PyTorch models with differential privacy

https://ai.facebook.com/blog/introducing-opacus-a-high-speed-library-for-training-pytorch-models-with-differential-privacy/

Github: https://github.com/pytorch/opacus

Differential Privacy Series Part 1 | DP-SGD Algorithm Explained: https://medium.com/pytorch/differential-privacy-series-part-1-dp-sgd-algorithm-explained-12512c3959a3

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scikit-learn Cookbook
Second Edition
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#book
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Machine learning – Linear Regression Course (Free)
.
Linear regression is perhaps one of the most popular and widely used algorithms in statistics and machine learning.
.
Link : https://bit.ly/31W6yH1

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Neural Networks and Deep Learning
A #Textbook
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The Little W-Net that Could

State-of-the-Art Retinal Vessel Segmentation with Minimalistic Models.

Github: https://github.com/agaldran/lwnet

Paper: https://arxiv.org/abs/2009.01907v1
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