365Data Science

Moving from Data Science to Machine Learning Engineering

The world of machine learning — and software — is changing. Read this article to find out how, and what you can do to stay ahead of it. Originally from KDnuggets https://ift.tt/3pcH8P7 source https://365datascience.weebly.com/the-best-data-science-blog-2020/moving-from-data-science-to-machine-learning-engineering

5 Reasons Why Containers Will Rule Data Science

Historically, containers were a way to abstract a software stack away from the operating system. For data scientists, containers have historically offered few benefits. Originally from KDnuggets https://ift.tt/3eJT6uA source https://365datascience.weebly.com/the-best-data-science-blog-2020/5-reasons-why-containers-will-rule-data-science

My Data Science Online Learning Journey on Coursera

Check out the author’s informative list of courses and specializations on Coursera taken to get started on their data science and machine learning journey. Originally from KDnuggets https://ift.tt/3k7FRoQ source https://365datascience.weebly.com/the-best-data-science-blog-2020/my-data-science-online-learning-journey-on-coursera

Deploy your first ML model live on WEB (Part 1)

Creating ML model for News Classification Photo by John Schnobrich on Unsplash This blog will be divided into four parts. Because I will try to explain the stuff from scratch so that if you have some basic knowledge about ML and python you do not need to wander here and there for deploying your first modelContinue reading “Deploy your first ML model live on WEB (Part 1)”

Universes that Learn: Cellular Automata Applications and Acceleration

Cellular Automata Applications and Acceleration For people with passing familiarity with the idea of cellular automata (CA), the first thing that comes to mind is probably John Horton Conway’s Game of Life. After Martin Gardner described Conway’s Game of Life (often abbreviated to Life, GOL, or similar) in his mathematical games column of Scientific AmericanContinue reading “Universes that Learn: Cellular Automata Applications and Acceleration”

Vision Transformersattention for vision task.

Vision Transformers — attention for vision task. Recently there’s paper “An Image is Worth 16×16 Words: Transformers for Image Recognition at Scale” on open-review. It uses pretrained transformers at scale for vision tasks. Transformers are highly successful for language tasks, but haven’t seen that much success for vision. In vision, transformers are either applied in conjunction with ConvolutionalContinue reading “Vision Transformersattention for vision task.”

Doing the impossible? Machine learning with less than one example

Machine learning algorithms are notoriously known for needing data, a lot of data — the more data the better. But, much research has gone into developing new methods that need fewer examples to train a model, such as “few-shot” or “one-shot” learning that require only a handful or a few as one example for effectiveContinue reading “Doing the impossible? Machine learning with less than one example”

Change the Background of Any Image with 5 Lines of Code

Blur, color, grayscale and change the background of any image with a picture using PixelLib. Originally from KDnuggets https://ift.tt/3eNdIST source https://365datascience.weebly.com/the-best-data-science-blog-2020/change-the-background-of-any-image-with-5-lines-of-code

Human vs. MachineReinforcement Learning in the Context of Snake

This blogpost elaborates on how to implement a reinforcement algorithm, which not only masters the game “Snake”, it even outperforms any… Continue reading on Becoming Human: Artificial Intelligence Magazine » Via https://becominghuman.ai/human-vs-machine-reinforcement-learning-in-the-context-of-snake-ae84d0b1f5d1?source=rss—-5e5bef33608a—4 source https://365datascience.weebly.com/the-best-data-science-blog-2020/human-vs-machinereinforcement-learning-in-the-context-of-snake

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