What Is Data Preparation in a Machine Learning Project
https://machinelearningmastery.com/what-is-data-preparation-in-machine-learning/

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! 🙌🏼