Creating Photo Mosaics Using Python
https://towardsdatascience.com/creating-photo-mosaics-using-python-49100e87efc

PULSE - Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models.

Research Paper: https://drive.google.com/file/d/1fV7FsmunjDuRrsn4KYf2Efwp0FNBtcR4/view

Code: https://github.com/adamian98/pulse

Other articles and sites:

https://techxplore.com/news/2020-06-artificial-intelligence-blurry-sharper.html

http://pulse.cs.duke.edu/

https://zentralwerkstatt.org/post_PULSE.html

https://towardsdatascience.com/explained-a-style-based-generator-architecture-for-gans-generating-and-tuning-realistic-6cb2be0f431

These fact checkers are LAME ASF

AnalyzeTheChat — Python-based WhatsApp chat analyzer
https://towardsdatascience.com/analyzethechat-python-based-whatsapp-chat-analyzer-cb53951c7ebb

SpineNet: A Novel Architecture for Object Detection Discovered with Neural Architecture Search
http://ai.googleblog.com/2020/06/spinenet-novel-architecture-for-object.html

🤯 What are tensors?

Learn from these amazing blogs:

👉🏼 A Gentle Introduction to Tensors for Machine Learning with NumPy by: Jason Brownlee. https://machinelearningmastery.com/introduction-to-tensors-for-machine-learning/

👉🏼 WTF is a Tensor?!? by: Matthew Mayo.
https://www.kdnuggets.com/2018/05/wtf-tensor.html

👉🏼 Quick ML Concepts: Tensors by: Chi Nok Enoch Kan.
https://towardsdatascience.com/quick-ml-concepts-tensors-eb1330d7760f

👉🏼 Our Instagram post covering this topic: https://www.instagram.com/p/CCSnIO9AVfd/?igshid=a2bgrgoip8zx

Happy learning! 🏁

👉🏼 Speech to text in Python with SpeechRecognition:

https://www.journaldev.com/37873/python-speech-to-text-speechrecognition

https://realpython.com/python-speech-recognition/

https://pypi.org/project/SpeechRecognition/

Face Detection using Haar Cascade Classifier:

https://docs.opencv.org/3.4/db/d28/tutorial_cascade_classifier.html

https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_objdetect/py_face_detection/py_face_detection.html

https://towardsdatascience.com/https-medium-com-dilan-jay-face-detection-model-on-webcam-using-python-72b382699ee9

OpenAI’s new language generator GPT-3 is shockingly good—and completely mindless
https://www.technologyreview.com/2020/07/20/1005454/openai-machine-learning-language-generator-gpt-3-nlp/

🤯 A Russian design firm passed off computer generated work as human, and it’s a peek at things to come.

👉🏼 How an AI graphic designer convinced clients it was human: https://thenextweb.com/neural/2020/07/16/how-an-ai-graphic-designer-convinced-clients-it-was-human/

👉🏼 Clients loved this designer’s work. Turns out, he was an AI: https://www.fastcompany.com/90528748/clients-loved-this-designers-work-turns-out-he-was-an-ai

👉🏼 Our Instagram post covering the topic: https://www.instagram.com/p/CC8cRRqgiaS/?igshid=1lc6mkzr0970i

👉🏼 Official website of the system: https://www.artlebedev.com/ironov/

👩🏻‍💻 Why should one study Linear Algebra for ML?

👉🏼 Clearly, to develop a better intuition for machine learning and deep learning algorithms and not treat them as black boxes. This would allow you to choose proper hyper-parameters and develop a better model. You would also be able to code algorithms from scratch and make your own variations to them as well.

👉🏼 Learn Linear Algebra for Machine Learning with:

Khan Academy: https://www.khanacademy.org/math/linear-algebra

Udacity: https://www.udacity.com/course/linear-algebra-refresher-course--ud953

Coursera: https://www.coursera.org/learn/linear-algebra-machine-learning

Here are some amazing freely available ebooks on the same topic:

Mathematics for Machine Learning: https://mml-book.github.io/book/mml-book.pdf

An Introduction to Statistical Learning: https://faculty.marshall.usc.edu/gareth-james/ISL/

Happy machine learning! 🎉

🤓 Free blog-course on machine learning!

https://www.c-sharpcorner.com/learn/learn-machine-learning-with-python

Hope y'all find it useful! 🙌🏼

🤯 A new model can detect deepfake images by looking at subtle visual artifacts like textures in hair, backgrounds and faces.

It creates heatmaps that pinpoint manipulated areas and exaggerate their effects.

Paper/Code: https://chail.github.io/patch-forensics/

🙌🏼 AutoML provides tools to automatically discover good machine learning model pipelines for a dataset with very little user intervention.

👉🏼 It is ideal for domain experts new to machine learning or machine learning practitioners looking to get good results quickly for a predictive modeling task. Open-source libraries are available for using AutoML methods with popular machine learning libraries in Python, such as the scikit-learn machine learning library.

👉🏼 In this tutorial, you will discover how to use top open-source AutoML libraries for scikit-learn in Python. Link: https://machinelearningmastery.com/automl-libraries-for-python/