Hands-On Transfer Learning with Python

Hands-On Transfer Learning with Python Implement Advanced Deep Learning and Neural Network Models Using TensorFlow and Keras (2018)

What you will learn in this book :

• Explore various DL architectures, including CNN, LSTM, and capsule networks
• Get to grips with models and strategies in transfer learning
• Walk through potential challenges in building complex transfer learning models from scratch
• Explore real-world research problems related to computer vision and audio analysis
• Understand how transfer learning can be leveraged in NLP

🌎 Github

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Another amazing deep learning cheatsheets, this time for Standford's CS 230 - Deep Learning class. A lot of materials covered from convolutional neural networks, recurrent neural networks to practical tips and tricks when training a neural network. Check out their Github repo to download all the materials as pdf or visit their website to read it directly from there.
#deeplearning #machinelearning #cheatsheets

Github: https://lnkd.in/dbiQAve
Website: https://lnkd.in/dpt8CNP

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by Vikas Gupta, we are sharing code (C++ and Python) to use OpenCV's built-in QR code Scanner.

We also compare it with Zbar QR code scanner. Unfortunately, OpenCV falls short, but hey it is a start!

🌎 https://lnkd.in/e9vdZM4

If you like it, please share it.

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Dive into Deep Learning

Jupyter Notebooks, PDF, and website, all generated from one source.

🌎 Link Review

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Data Science: AI Flowchart

~ The vast majority of the AI advancements and applications you hear about refer to a category of algorithms known as machine learning.
~ Machine-learning algorithms use statistics to find patterns in massive amounts of data. And data, here, encompasses a lot of things—numbers, words, images, clicks, what have you. If it can be digitally stored, it can be fed into a machine-learning algorithm.
~ The AI Flowchart, in the post image, is good, given most of the stuff written about AI found on the internet is nonsense.
~ My post about "Data Science: Skills You Actual Need" has drawn the most viewes and comments, not because of its great content, but its absurd content. Go to: https://lnkd.in/dYdMG2E
~ Regarding post re "The Weaknesses Of Variable Selection, Part I,
go to: https://lnkd.in/emxJBYd
~ Regarding post re "The Weaknesses Of Variable Selection, Part II
go to: https://lnkd.in/eBJhgXG
--- B. Noted

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دوره های رایگان یادگیری ماشین آمازون

Amazon makes its machine learning courses available for free

You can check out all of Amazon’s machine learning courses.
#یادگیری_ماشین #ml #منابع
🌎 Link Review
🌎 All link

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✅ اسلایدها و ویدئو ها از کنفرانس
The Scaled Machine Learning Conference 2018
#کنفرانس #یادگیری_ماشین #آموزش #مقاله #منابع

1️⃣ Introduction slide
🔸 Scaled Machine Learning
🔸 Video

2️⃣ RL Systems by Ion Stoica Slides :
🔸 Slide
🔸 Video

3️⃣ Computer Vision Made Simple by Reza Zadeh
🔸 Slides
🔸 Video

4️⃣ Machine Learning for Biomedicine at Scale by Jennifer Chayes
🔸 Slides
🔸 Video

5️⃣ Systems and Machine Learning" by Jeff Dean
🔸 Slides
🔸 Video

6️⃣ Role of Tensors in Large-Scale Machine by Anima Anandkumar
🔸 Slides
🔸 Video

7️⃣ Meta Learning & Self Play by Ilya Sutskever
🔸 Slides
🔸 Video

8️⃣ Large-scale Deep Learning with Keras by Francois Chollet
🔸 Slides
🔸 Video

9️⃣ Scaling of Machine Learning by Bill Dally
🔸 Slides
🔸 Video

🔟 Specialized Deep Learning with Graphcore by Simon Knowles
🔸 Slides
🔸 Video

☑️ Machine Learning at Facebook: An Infrastructure View by Yangqing Jia
🔸 Slides
🔸 Video

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🗣 @AI_Python_arXiv
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Painting with GANPaint!
Link
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🗣 @AI_Python_arXiv
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Andrew Ng
Our new result in PLOSMedicine: DL to help radiologists w/knee MRI diagnosis, comparing Human+Machine vs. Human alone. Hope systems like these can soon be deployed and help patients!



https://stanfordmlgroup.github.io/projects/mrnet/

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what AI can Does?

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Deep learning made easier with transfer learning
#انتقال_یادگیری
🌎 http://bit.ly/2xKzQs3

#AI #DeepLearning #MachineLearning #DataScience

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Guide to learn DataScience and MachineLearning with Python:
#ML #DL
#منابع #علم_داده
---START---

✅ Step 1

🔸 Download and Install Anaconda

✅ Step 2
a. Learn the basics of Python (Lists, Tuples, Dictionaries, etc)
b. Understand the basics of data structures and algorithms :

🌎 Link Review
---Beginner Level Completed---

✅ Step 3
a. Understand the use of regular expressions
🔸 Do more practice problems in PythonHacker Rank
🔸 Codeacademy

✅ Step 4
Learn the scientific libraries (NumPy, SciPy, Pandas)
🔸 Pandas

✅ Step 5
Data Visualization (Matplotlib, plotly, seaborne, etc…)
🔸 Matplotlib
🔸 Python Gallery
---Intermediate Level Done---

✅ Step 6
🔸Machine Learning with Scikit-LearnMachine Learning in 20min
🔸 Skcikit-Learn Tutorial

✅ Step 7:
Practice your machine learning skillsKaggle Machine Learning Tutorial
---Advanced Level Completed--

✅ Step 8:
Deep Learning
Deeplearning.ai (Andrew Ng)

🔸 Kaggle Deep Learning Tutorial

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GAN Dissection is a way to inspect the internal representations of a generative adversarial network (GAN) to understand how internal units align with human-interpretable concepts. It is part of NetDissect.


https://github.com/CSAILVision/GANDissect

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Machine Learning Open Source of the Month (v.Nov 2018)

Topics: NLP, Hentai, Applied RL, Reinforcement Learning, Deep Learning, Automl, Graph Networks, MAME RL Algorithm, Model Compression, R-CNN

Open source projects can be useful for programmers. Hope you find an interesting project that inspires you.
اموزش های یادگیری ماشین
#منابع #یادگیری_ماشین
#NLP
#AI #DeepLearning #MachineLearning #DataScience

🌎 Link Review

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What happens when computers can see?

Say Hi to Azka, an A.I that can track, and analyze human movement, with a myriad of consumer analytics and retail applications.



Read more, on what tis the potential of Computer Vision Here:

https://lnkd.in/d-vqtwc

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Artificial Intelligence, Machine Learning and Radiomics in Radiology and Article held in Chicago 2018

The use of artificial intelligence (AI) in radiology – radiomics – has been getting a lot of attention, fuelled by the availability of large datasets, substantial advances in computing power, and new deep-learning algorithms. This has led to a rapid rise in the potential use of artificial intelligence in various radiological imaging tasks. Machine learning in radiology, a subset of artificial intelligence, is expected to have a substantial clinical impact, with the imaging examinations routinely obtained in clinical practice providing an opportunity to improve decision support in medical image interpretation.


🌎 Article collection


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WaveNet: Google Assistant’s Voice Synthesizer.

#DataScience #MachineLearning
#ArtificialIntelligence

🌎 http://bit.ly/2BzuIKn


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Getting Started With MarathonEnvs v0.5.0a

Blog by Joe Booth: https://lnkd.in/evx6Wme

#MachineLearning #ArtificialIntelligence #DeepLearning #NeuralNetworks #Robotics

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Linux and Supercomputers | Link

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Introduction to Applied Linear Algebra – Vectors, Matrices, and Least Squares

By Stephen Boyd and Lieven Vandenberghe, Cambridge University Press:

https://lnkd.in/eQnqVQ9

#ArtificialIntelligence #LinearAlgebra #Vectors #Matrices #MachineLearning #AI

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✴️ @AI_Python_EN

Fantastic new resource on GANs from MIT, Google, and others: GAN Dissection, Visualizing and Understanding Generative Adversarial Networks.

Code, paper, website at:

https://lnkd.in/fzP79hZ

#ArtificialIntelligence #GAN #MachineLearning #AI

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