The big yellow school bus, with its plastic seats, rubbery smell, and cool-kids-in-the-back social hierarchies, hasn't gotten a true update in decades. What will happen to such an old-fashioned vehicle when our streets become flooded with driverless cars? We know how service vehicles like delivery vans and city buses will be affected by autonomous tech. What about school buses, which are so vital and also so fraught with concerns over safety? Will parents ever trust an autonomous vehicle enough to allow their children to ride in one with no human supervision?

About this course: The manufacturing industry is making a digital transformation, allowing companies to customize production through advances in machine learning, sustainable design, generative design, and collaboration, with integrated design and manufacturing processes. This course introduces innovations in CAD and digital manufacturing, speaking to the rapid changes taking place that are forever transforming the future of making. This course will also explore foundational concepts behind Autodesk Fusion 360 CAD/CAM. Fusion 360 is a cloud-based CAD/CAM tool for collaborative product development that combines industrial design, mechanical engineering, and machine tool programming into one software solution. Through a series of lectures and hands-on exercises, this course provides the core philosophy behind the software.

About this course: Most professions these days require more than general intelligence. They require in addition the ability to collect, analyze and think about data. Personal life is enriched when these same skills are applied to problems in everyday life involving judgment and choice. This course presents basic concepts from statistics, probability, scientific methodology, cognitive psychology and cost-benefit theory and shows how they can be applied to everything from picking one product over another to critiquing media accounts of scientific research. Concepts are defined briefly and breezily and then applied to many examples drawn from business, the media and everyday life.

About this course: Want to understand your data network structure and how it changes under different conditions? Curious to know how to identify closely interacting clusters within a graph? Have you heard of the fast-growing area of graph analytics and want to learn more? This course gives you a broad overview of the field of graph analytics so you can learn new ways to model, store, retrieve and analyze graph-structured data. After completing this course, you will be able to model a problem into a graph database and perform analytical tasks over the graph in a scalable manner.

About this course: In this course, application developers learn how to design, develop, and deploy applications that seamlessly integrate components from the Google Cloud ecosystem. Through a combination of presentations, demos, and hands-on labs, participants learn how to use GCP services and pre-trained machine learning APIs to build secure, scalable, and intelligent cloud-native applications.

To the editor: I read "Do L.A. Unified's daily random searches keep students safe, or do they go too far?" and shuddered. Los Angeles Unified School District officials should be ashamed and embarrassed over the dehumanizing way they treat students. How can anyone connected with this fiasco condone such an assault on their students' personhood or create such a threatening environment so adverse to learning? Parents and students have complained, community groups have protested, the American Civil Liberties Union has become involved, but nothing changes. Perhaps now with the curtain pulled back for the broader public to see, this mean-spirited breach of trust in the name of safety will be stopped.

Machine Learning is a growing field that focuses on teaching computers to do work that was traditionally reserved for humans. It is a cross-functional domain that uses concepts from statistics, math, software engineering, and more. R language is widely used among statisticians and data miners to develop statistical software and perform data analysis. So, if you're looking at mastering the techniques of machine learning, then go for this Learning Path. Packt's Video Learning Path is a series of individual video products put together in a logical and stepwise manner such that each video builds on the skills learned in the video before it.

In 2017, people flocked to online classes about artificial intelligence, cryptocurrency, and data analytics. In 2018, expect more of the same, say leading online-education providers Codecademy, Coursera, edX, and Udacity. In response to a request from MIT Technology Review, they calculated their most popular courses of the past year and revealed which topics they think will lure the most students in the next. More than 29 million people have registered to take classes at Coursera, an online platform that hosts more than 2,000 courses from universities such as Stanford and Yale. Nikhil Sinha, the company's chief content officer, says many who enroll are "looking for a leg up in their careers" and gravitate to the platform's "cutting-edge tech" courses.

Users will be taken through a journey that starts by showing them the various algorithms that can be used for reward-based learning. The video describes and compares the range of model-based and model-free learning algorithms that constitute RL algorithms. The Course starts by describing the differences in model-free and model-based approaches to Reinforcement Learning. We look at model-based approaches to Reinforcement Learning.We discuss State-value and State-action value functions, Model-based iterative policy evaluation, and improvement, MDP R examples of moving a pawn, how the discount factor, gamma, "works" and an R example illustrating how the discount factor and relative rewards affect policy. Next, we learn the model-free approach to Reinforcement Learning.This includes Monte Carlo approach, Q-Learning approach, More Q-Learning explanation and R examples of varying the learning rate and randomness of actions and SARSA approach. Finally, we round things up by taking a look at model-free Simulated Annealing and more Q-Learning algorithms.

Are You an Ecologist or Conservationist Interested in Learning GIS and Machine Learning in R? Then this course is for you! I will take you on an adventure into the amazing of field Machine Learning and GIS for ecological modelling. You will learn how to implement species distribution modelling/map suitable habitats for species in R. My name is MINERVA SINGH and i am an Oxford University MPhil (Geography and Environment) graduate. I finished a PhD at Cambridge University (Tropical Ecology and Conservation). I have several years of experience in analyzing real life spatial data from different sources and producing publications for international peer reviewed journals.