Author Archives: 365Data Science

Why do we use probability distributions, and why do they matter? Originally from KDnuggets https://ift.tt/2Zyonuz source https://365datascience.weebly.com/the-best-data-science-blog-2020/before-probability-distributions

Source If you want to deploy your TensorFlow model to a mobile or embedded device, a large model may take too long to download and use too much RAM and CPU, all of which will make your app unresponsive, heat the device and drain its battery. To avoid this, you need to make a mobile-friendly.Continue reading “Deploy a TensorFlow Model to a Mobile or an Embedded Device”

Examining the moral agency of AI How do self-driving cars decide who to kill in a road accident, and how many? Self-driving vehicles are now on our roads and increasing in number. Ranging from Minis to semi-trailer trucks, autonomous vehicles issue in a whole new age of road transportation whereby human drivers can literally let go ofContinue reading “How moral are self-driving cars?”

Based on 527 placebo-controlled studies, here are 5 science-backed supplements for improving memory Continue reading on Becoming Human: Artificial Intelligence Magazine » Via https://becominghuman.ai/top-5-best-nootropics-for-memory-in-healthy-people-according-to-science-7093cc18425c?source=rss—-5e5bef33608a—4 source https://365datascience.weebly.com/the-best-data-science-blog-2020/top-5-best-nootropics-for-memory-in-healthy-people-according-to-science

As a Data Scientist, you are already spending most of your time getting your data ready for prime time. Follow these real-world scenarios to learn how to leverage the advanced techniques in Python of list comprehension, Lambda expressions, and the Map function to get the job done faster. Originally from KDnuggets https://ift.tt/2ZyWXoB source https://365datascience.weebly.com/the-best-data-science-blog-2020/3-advanced-python-features-you-should-know

A couple of years ago, Google published one of the most seminal papers in machine learning interpretability. Originally from KDnuggets https://ift.tt/3h611T2 source https://365datascience.weebly.com/the-best-data-science-blog-2020/understanding-how-neural-networks-think

Free MIT Courses on Calculus: The Key to Understanding Deep Learning; How Much Math do you need in Data Science? My Biggest Career Mistake In Data Science; Mathematics for Machine Learning: The Free eBook Originally from KDnuggets https://ift.tt/2OwxeXi source https://365datascience.weebly.com/the-best-data-science-blog-2020/top-kdnuggets-tweets-jul-8-14-free-mit-courses-on-calculus-the-key-to-understanding-deep-learning

This hands-on book bridges the gap between theory and practice, showing you the math of deep learning algorithms side by side with an implementation in PyTorch. Save 50% off Math and Architectures of Deep Learning with code kdarch50. Originally from KDnuggets https://ift.tt/3fyx79A source https://365datascience.weebly.com/the-best-data-science-blog-2020/math-and-architectures-of-deep-learning6865244

This post looks at research undertaken to provide interactive business intelligence reports and visualizations for thousands of end users, in the hopes of addressing some of the challenges to architects and engineers looking at moving to Google Cloud Platform in selecting the best technology stack based on their requirements and to process large volumes ofContinue reading “Apache Spark on Dataproc vs. Google BigQuery”

In this work I have tried to showcase the housing prices in Californi, datasets are available: GitHub Continue reading on Becoming Human: Artificial Intelligence Magazine » Via https://becominghuman.ai/housing-price-with-scikit-learns-stratifiedshufflesplit-2291c8be456f?source=rss—-5e5bef33608a—4 source https://365datascience.weebly.com/the-best-data-science-blog-2020/housing-price-with-scikit-learns-stratifiedshufflesplit