On May 8, 2018, Google I/O was held at Shoreline Amphitheatre in Mountain View, California. If you are wondering what Google I/O is, don't worry, I've got your back. "Google I/O brings together developers from around the globe annually for talks, hands-on learning with Google experts, and the first look at Google's latest developer products." In the Keynote, Sundar Pichai, the CEO of Alphabet Inc. (Google's parent company), shared the then-latest developments that Google had been working on. One of the projects that he spoke about was something that maybe no one saw coming; an application of Artificial Intelligence (AI), soon to be on our own smartphones, that left the world in awe.
The concept of transfer learning lies in imparting knowledge learned for performing a task to another task that is different but similar. How is Transfer Learning Useful to Me? In the context of humans, transfer learning is crucial to our lives. Let us use the CIFAR-10 dataset that contains 10 categories of images -- airplane, automobile, bird, cat, deer, dog, frog, horse, ship and truck. Our task of interest is to classify every image to its corresponding category.
When most people hear the term Artificial Intelligence, the first thing they usually think of is robots or some famous science fiction movie like the Terminator depicting the rise of AI against humanity. Artificial intelligence refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning, analyzing, comprehending, and problem-solving. The applications of artificial intelligence in the real-world are perhaps more than what many people know. The ideal characteristic of artificial intelligence is its ability to rationalize and take actions that have the best chance of achieving a specific goal or defined operations. With the advancements of the human mind and their deep research into the field, AI is no longer just a few machines doing basic calculations.
Are you a programmer who wants to understand how to customize Conversational Chat bots programmatically on the YM platform? In this course, you will learn the core Programming concepts of YM Platform known as Cloud Functions in order to customize your Chat bot. You will write custom logic using Cloud Function – Objects and methods, and test that logic using the built-in testing tool. You will explore how Cloud Functions interacts with UI of the platform. You will get hands-on experience writing code to customize your chat bot interface to support different channels, as well as a brief introduction to the built in Database.
If you have ever done a Kaggle competition, these would be commonly referred to as evaluation metrics. Typically, the lower the loss, the better the performance of your model. So if,for example, you were predicting house prices and using Mean Squared Error, and your cost was $25000, that means that your model is performing poorly as it is making a prediction error of $25000. Going back to our analogy, if you imagine that instead of a mountain there is a U-shaped curve, and instead of a person there is the cost function with maybe an initial cost value of 25,500. The aim of Gradient Descent would be to minimise this cost to either 0(global minimum), or something much smaller(local minimum).
Finland has released a free online artificial intelligence (AI) course which aims to educate public administration, businesses and the general public about the technology and to consider what it should be used for. The Ethics of AI course offered by the University of Helsinki has been designed in a partnership with the cities of Helsinki, Amsterdam and London as well as Finland's Ministry of Finance. Questions pertaining to the ethics of AI are topical, as many people are already making ethical choices in their work, for example, on data use. The course sets out to help them understand what the ethical use of artificial intelligence means and what it requires from both society and individuals. "These questions include how our data is used, who is responsible for decisions made by computers and whether, say, facial recognition systems are used in a way that acknowledges human rights. In a broader sense, it's also about how we wish to utilise advancing technical solutions," said Anna-Mari Rusanen, course coordinator for Ethics of AI.
Researchers at the Allen Institute for Artificial Intelligence have developed an AI-powered model that summarises scientific papers into a few sentences. In other words, it condenses a research paper into TLDR (Too Long; Didn't Read) format so you can decide which papers are worth reading. It does this by extracting the most important parts from the abstract, introduction, and conclusion sections, creating a snippet to describe the paper.
Add in a dash of Data Science tinkering ("I think I ran my Jupyter Notebook cells out of order") -- and it's no surprise 9 out of 10 Data Science projects never see the light of day. Given that the only data product I've deployed thus far is this clustering-based Neighborhood Explorer dashboard, I'll leave it to the more experienced to walk you through the deployment process. Data Scientists should understand how to deploy and scale their own models…Overspecialization is generally a mistake. She recommends courses and reading material on Kubernetes for Data Science. This container management tool represents the dominant force in cloud deployment.
Online Courses Udemy - All-in-One:Machine Learning,DL,NLP,AWS Deply [Hindi][Python], Complete hands-on Machine Learning Course with Data Science, NLP, Deep Learning and Artificial Intelligence Created by Rishi Bansal English Students also bought Java from Zero to First Job: Part 1 - Java Basics and OOP C Programming for Beginners - Master the C Fundamentals Full-Stack Web Development For Beginners The Complete Java Programmer: From Scratch to Advanced Python and Django Full-Stack Web Development for beginners Learn To Create AI Assistant (JARVIS) With Python Preview this course GET COUPON CODE Description This course is designed to cover maximum Concept of Machine Learning. Anyone can opt for this course. No prior understanding of Machine Learning is required. As a Bonus Introduction Natural Language Processing and Deep Learning is included. Below Topics are covered Chapter - Introduction to Machine Learning - Machine Learning?