Machine learning is the foundation for predictive modeling and artificial intelligence. If you want to learn about both the underlying concepts and how to get into building models with the most common machine learning tools this path is for you. In this course, you will learn the core principles of machine learning and how to use common tools and frameworks to train, evaluate, and use machine learning models. This course is designed to prepare you for roles that include planning and creating a suitable working environment for data science workloads on Azure. You will learn how to run data experiments and train predictive models. In addition, you will manage, optimize, and deploy machine learning models into production.
Machine Learning with AWS is the right place to start if you are a beginner interested in learning useful artificial intelligence (AI) and machine learning skills using Amazon Web Services (AWS), the most popular and powerful cloud platform. You will learn how to use AWS to transform your projects into apps that work at high speed and are highly scalable. From natural language processing (NLP) applications, such as language translation and understanding news articles and other text sources, to creating chatbots with both voice and text interfaces, you will learn all that there is to know about using AWS to your advantage. You will also understand how to process huge numbers of images fast and create machine learning models. By the end of this course, you will have developed the skills you need to efficiently use AWS in your machine learning and artificial intelligence projects.
Artificial intelligence (AI) has become a part of everyday conversation and our lives. It is considered as the new electricity that is revolutionizing the world. AI is heavily invested in both industry and academy. However, there is also a lot of hype in the current AI debate. AI based on so-called deep learning has achieved impressive results in many problems, but its limits are already visible. AI has been under research since the 1940s, and the industry has seen many ups and downs due to over-expectations and related disappointments that have followed. The purpose of this book is to give a realistic picture of AI, its history, its potential and limitations. We believe that AI is a helper, not a ruler of humans. We begin by describing what AI is and how it has evolved over the decades. After fundamentals, we explain the importance of massive data for the current mainstream of artificial intelligence. The most common representations for AI, methods, and machine learning are covered. In addition, the main application areas are introduced. Computer vision has been central to the development of AI. The book provides a general introduction to computer vision, and includes an exposure to the results and applications of our own research. Emotions are central to human intelligence, but little use has been made in AI. We present the basics of emotional intelligence and our own research on the topic. We discuss super-intelligence that transcends human understanding, explaining why such achievement seems impossible on the basis of present knowledge,and how AI could be improved. Finally, a summary is made of the current state of AI and what to do in the future. In the appendix, we look at the development of AI education, especially from the perspective of contents at our own university.
Artificial intelligence (AI) and machine learning (ML) have become more popular in Vietnam with a large proportion of young people having dabbled in these fields after realizing their potential. CoderSchool, a startup in virtual programming and education in Vietnam, has recently received a U$$2.6 million investment in the pre-Series A fund rounds to expand their scope. In response to the Industrial Revolution 4.0, the needs for workers in technology have tremendously increased. A lot of young people have left their comfort zone and entered the AI and ML fields. Nguyen The Chinh, 35, is a former manager in the technical department of a multinational corporation. He switched to AI and ML and signed up for a three-month bootcamp course.
Then this course is for you!! This course has been practically and carefully designed by industry experts to offer the best way of learning Data Science and Machine Learning the practical way with hands-on projects throughout the course. This course will help you learn complex Data Science concepts and machine learning algorithms the practical way for easier understanding. We will walk you through step-by-step on each topic explaining each line of code for your understanding. There is going to be a lot of fun, exciting, and robust projects to better understand each concept under each topic.
There is mounting public concern over the influence that AI based systems has in our society. Coalitions in all sectors are acting worldwide to resist hamful applications of AI. From indigenous people addressing the lack of reliable data, to smart city stakeholders, to students protesting the academic relationships with sex trafficker and MIT donor Jeffery Epstein, the questionable ethics and values of those heavily investing in and profiting from AI are under global scrutiny. There are biased, wrongful, and disturbing assumptions embedded in AI algorithms that could get locked in without intervention. Our best human judgment is needed to contain AI's harmful impact. Perhaps one of the greatest contributions of AI will be to make us ultimately understand how important human wisdom truly is in life on earth.
Goto: Amazon DynamoDB: Building NoSQL Database-Driven ApplicationsThis course introduces you to NoSQL databases and the challenges they solve. Expert instructors will dive deep into Amazon DynamoDB topics such as recovery, SDKs, partition keys, security and encryption, global tables, stateless applications, streams, and best practices. DynamoDB is a key-value and document database that delivers single-digit millisecond performance at any scale. It's a fully managed, multiregion, multimaster database with built-in security, backup and restore, and in-memory caching for internet-scale applications. DynamoDB can handle more than 10 trillion requests per day and support peaks of more than 20 million requests per second.
Then this course is for you!! This course has been practically and carefully designed by industry experts to offer the best way of learning Data Science and Machine Learning the practical way with hands-on projects throughout the course. This course will help you learn complex Data Science concepts and machine learning algorithms the practical way for easier understanding. We will walk you through step-by-step on each topic explaining each line of code for your understanding. There is going to be a lot of fun, excited, and robust projects to better understand each concept under each topic.
Developers and business leaders can learn about the latest trends in artificial intelligence (AI) at IBM's free Data & AI digital conference on Nov. 10 starting at 2 pm GMT. The sessions will focus on operations, ethics, and cloud computing. IBM is running the conference again on Nov. 24 for India and the Asia Pacific region. People who register for the conference get $300 in credits to spend on any services in the IBM Cloud Catalog. Attendees who completes the course in Track 3 earn an AI and Data Essentials badge.