In this course, we aim to specialize in artificial intelligence by doing Machine Learning and Deep Learning Projects at various levels. Before starting the course, you must have basic Python knowledge. Our aim in this course is to turn real-life problems that seem difficult to do into projects and then solve them using latest versions of artificial intelligence algorithms and Python(3.8). This course was prepared in July 2021. We will carry out some of our projects using machine learning and some using deep learning algorithms.

It's one thing to have sensors, it's another to extract value from them. As businesses across all sectors take their first steps toward Industrial IoT and edge computing solutions, extracting machine/sensor data and making it available for things like predictive maintenance and condition-based monitoring can prove challenging. The gap between OT and IT is widest at the edge – factories, oil rigs, wind farms, water treatment plants and more. In this webinar, we'll explain how an IIoT edge hub bridges the gap by collecting, parsing and storing machine/sensor data, and making it accessible via standard protocols such as MQTT and SQL – all without the need to write a single line of code. If you have already registered, click here to access.

Watson is among millions of teachers across the nation who are in their second year of teaching either in-person, online or both -- depending on the state, city and district they live in. Like many other professions, teachers' jobs have become increasingly complex due to the pandemic. This year, many students are back in the classroom, but teachers have to constantly adapt if there is virus exposure. There aren't specific guidelines on how best to teach students using the many technologies that are available. Teachers are also struggling to keep students engaged while learning new tech tools that are required to make online classes successful.

Artificial Intelligence for Business, Solve Real World Business Problems with AI Solutions Rating: 4.5 out of 5 Created by Hadelin de Ponteves, Kirill Eremenko, SuperDataScience Team English [Auto], French [Auto]Preview this Course - GET COUPON CODE Structure of the course: Part 1 - Optimizing Business Processes Case Study: Optimizing the Flows in an E-Commerce Warehouse AI Solution: Q-Learning Part 2 - Minimizing Costs Case Study: Minimizing the Costs in Energy Consumption of a Data Center AI Solution: Deep Q-Learning Part 3 - Maximizing Revenues Case Study: Maximizing Revenue of an Online Retail Business AI Solution: Thompson Sampling Real World Business Applications: With Artificial Intelligence, you can do three main things for any business: Optimize Business Processes We will show you exactly how to succeed these applications, through Real World Business case studies. And for each of these applications we will build a separate AI to solve the challenge. In Part 1 - Optimizing Processes, we will build an AI that will optimize the flows in an E-Commerce warehouse. In Part 2 - Minimizing Costs, we will build a more advanced AI that will minimize the costs in energy consumption of a data center by more than 50%! Just as Google did last year thanks to DeepMind.

If you are looking to start your career in machine learning then this is the course for you. This is a course designed in such a way that you will learn all the concepts of machine learning right from basic to advanced levels. For the code explained in each lecture, you can find a GitHub link in the resources section. Machine learning is the fuel we need to power robots, alongside AI. With Machine Learning, we can power programs that can be easily updated and modified to adapt to new environments and tasks to get things done quickly and efficiently.

Video Production can be time-consuming, difficult, technical and expensive, but it doesn't have to be. This video production course is about how to do simple, easy talking head videos for a wide range of business communication needs. There is a video explosion going on in the online world. Are you unsure where to start? This course will lead you through the simplest and easiest ways to start communicating with your customers, clients, prospects and colleagues in the most effective manner: talking head video.

It is simply looking at where things happen to understand why they happen there. Geospatial Data Science is the discipline that specifically focuses on the spatial component of data science. Spatial Analysis is considered as a core infrastructure of the modern tech industry and is heavily substantiated by the business transactions of world-leading companies such as Uber, Deliveroo, Apple, Google, Intel, and evidently by the motor companies such as Tesla, BMW, and Mercedes. So, these companies are bound to hire more and more Spatial Data Analysts and Geo-Spatial Scientists. Based on these business trends, we've compiled the spatial analysis courses designed by world-class educators to help beginners gain solid foundations of spatial data analysis.

In this course, our intent is to provide just the right information to get you started on some of key technologies - Internet of Things, Blockchain, Cloud and Artificial Intelligence. The combinatorial power of these technologies would drive next generation of future applications. Internet of Things (IoT) is one of the most hyped concepts in today's technology world. However, with so much hype, there is still a lot of confusion on what does Internet of Things actually mean and what it takes to build IoT applications and how to apply it in various industries. The first topic would cover what is Internet of Thing, followed by how to realize IoT applications using an Internet of Things Architecture.

Build an image-classifier system that makes human-like decisions. Most computer vision-related tutorials jump right to implementation after a few cursory introductory notes. What sets Raveena Jayadev's post apart is that we do get a thorough, hands-on guide to building a machine learning system that recognizes digits, but not before we first understand how that system's "mental model" operates. Get a solid foundation in online (machine) learning. A popular deep learning topic, online learning has numerous industry applications in scenarios where models "must learn from new data that is constantly becoming available," as Cameron Wolfe explains in his essential (and comprehensive) introduction to the topic.

Deep Learning: Recurrent Neural Networks with Python Recurrent Neural Networks (RNNs), a class of neural networks, are essential in processing sequences such as sensor measurements, daily stock prices, etc. Description Recurrent Neural Networks (RNNs), a class of neural networks, are essential in processing sequences such as sensor measurements, daily stock prices, etc. In fact, most of the sequence modelling problems on images and videos are still hard to solve without Recurrent Neural Networks. Further, RNNs are also considered to be the general form of deep learning architecture. Hence, the understanding of RNNs is crucial in all the fields of Data Science. This course addresses all these concerns and empowers you to take your career to the next level with a masterful grip on the theoretical concepts and practical implementations of RNNs in Data Science.