While her peers reveled in an unprecedented virtual school year, the self-described "technology enthusiast," Harita Suresh, 13, was bored. She decided on an online course and settled on IBM Skills Network's "AI chatbots without programming." She lacked experience with artificial intelligence, but was eager to learn through the self-paced course. Harita is more than a little familiar with tech, "I have been interested in technology since I was 5," she said. "My first coding challenge was the Lightbot Hour of Code. I was fascinated that the code I wrote could control the actions of the characters on screen. Since then, I pursued coding on multiple platforms like code.org, The more I learned about tech, the more I wanted to know. In fifth grade, I took a Python programming course offered by Georgia Tech."

Staying healthy and fit is a critical habit to build (especially in the midst of a global pandemic). Unfortunately, without the amenities of our everyday fitness routines-- lavish community gyms, expert personal trainers, even that one buddy who spends way too much time working out-- staying in shape can be a struggle for many. But what if you could have 24/7 access to expert-level, on-demand personal training advice, as quickly and easily as sending a text message? Thanks to increasingly sophisticated conversational AI technologies, it's now possible to build your very own virtual workout advisor in just minutes (even if you have no clue how to code). In this tutorial, we're going to walk through the process of creating an AI personal trainer using IBM's Watson Assistant.

Millions of tickets arrive at Uber's customer service department every week from its riders, drivers, eaters, etc. It is important for Uber to handle these tickets in a quick and efficient manner to retain its customers and fuel the companies growth. For this purpose, Uber has designed COTA or'Customer Obsession Ticket Assistant'. COTA is a Machine Learning and NLP powered tool that enables quick and efficient issue resolution of more than 90 per cent of Uber's inbound support tickets. For detailed information about different processes in the pipeline, please refer to this article by Uber. Uber is known to organize its processes using Machine Learning to achieve high speed and accuracy.

The world of UI/UX is changing every month. What if you could use machine learning to help you keep up with all of the changes? Machine learning can help developers make more user-friendly web applications. Learn some background on machine learning and algorithms and see examples of where Brain.js The world of UI/UX is changing every month.

In this course I am going to introduce you to Watson Studio AutoAI by IBM. Artificial Intelligence (AI) and Machine Learning (ML) are two very hot topics nowadays. Experts claim that AI & ML are going to revolutionize the world. This course is designed for those who want to take a short cut to these technologies. Auto AI and Auto ML are new tools that provide methods and processes to make Artificial intelligence and Machine Learning available for non-experts.

While her peers reveled in an unprecedented virtual school year, the self-described "technology enthusiast," Harita Suresh, 13, was bored. She decided on an online course and settled on IBM Skills Network's "AI chatbots without programming." She lacked experience with artificial intelligence, but was eager to learn through the self-paced course. Harita is more than a little familiar with tech, "I have been interested in technology since I was 5," she said. "My first coding challenge was the Lightbot Hour of Code. I was fascinated that the code I wrote could control the actions of the characters on screen. Since then, I pursued coding on multiple platforms like code.org, The more I learned about tech, the more I wanted to know. In fifth grade, I took a Python programming course offered by Georgia Tech."

AWS has made its CodeGuru tool generally available for developers. The tool, initially released in preview at the AWS re:Invent conference last December, uses machine learning to make recommendations on how developers can improve the quality of their code quality, as well as identify an application's most expensive lines of code. "CodeGuru helps you improve your application code and reduce compute and infrastructure costs with an automated code reviewer and application profiler that provide intelligent recommendations," said Danilo Poccia, chief evangelist for the EMEA region at AWS, in a blog post. "Using visualizations based on runtime data, you can quickly find the most expensive lines of code of your applications. With CodeGuru, you pay only for what you use."

AWS has made its CodeGuru tool generally available for developers. The tool, initially released in preview at the AWS re:Invent conference last December, uses machine learning to make recommendations on how developers can improve the quality of their code quality, as well as identify an application's most expensive lines of code."CodeGuru "Using visualizations based on runtime data, you can quickly find the most expensive lines of code of your applications. With CodeGuru, you pay only for what you use."CodeGuru has two main components: CodeGuru Reviewer and CodeGuru Profiler.CodeGuru Reviewer improves code quality by scanning for critical issues and identifying bugs. The managed service then recommends ways a developer can fix these issues.Meanwhile, CodeGuru Profiler helps programmers find an application's most expensive lines of code.

The goal is to dramatically improve the trustworthiness of the data being relied on to prescriptively automate business processes in real time. IBI this week during a Virtual Sumit 2020 event this week outlined a strategy that revolves around machine learning algorithms and other forms of artificial intelligence (AI) to embed real-time analytics into business processes. Formerly known as Information Builders, the goal is to dramatically improve the trustworthiness of the data being relied on to prescriptively automate business processes in real time, says IBI CEO Frank Vella. At the core of that strategy is an Open Data Platform from IBI that enables applications to embed data visualization capabilities that are connected in real time to various data sources, file formats, and applications, including rival data visualizations tools from Microsoft and Tableau Software. While IBI continues to provide its own Focus and WebFocus tools for visualizing data, Vella says rather than forcing organizations to abandon existing data visualization tools it makes more sense to invoke an enterprise-class data analytics backend engine developed by IBI via those tools.

Obviously, GLTR is not perfect. Its main limitation is its limited scale. It won't be able to automatically detect large-scale abuse, only individual cases. Moreover, it requires at least an advanced knowledge of the language to know whether an uncommon word does make sense at a position. Our assumption is also limited in that it assumes a simple sampling scheme.