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.
Apache Spark is the de-facto standard for large scale data processing. This is the first course of a series of courses towards the IBM Advanced Data Science Specialization. We strongly believe that is is crucial for success to start learning a scalable data science platform since memory and CPU constraints are to most limiting factors when it comes to building advanced machine learning models. In this course we teach you the fundamentals of Apache Spark using python and pyspark. We'll introduce Apache Spark in the first two weeks and learn how to apply it to compute basic exploratory and data pre-processing tasks in the last two weeks.
The following content is brought to you by ZDNet partners. If you buy a product featured here, we may earn an affiliate commission or other compensation. Artificial intelligence (AI) has become so commonplace that it's easy to forget it was once a science fiction pipe dream. But AI and the machine learning concepts behind it are still new enough that programmers and data scientists will be in demand for the foreseeable future. So if you want to pursue a career in one of the fields where data science know-how is essential, this e-learning bundle can serve as a great first step.
If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This Specialization will teach you best practices for using TensorFlow, a popular open-source framework for machine learning. In Course 3 of the deeplearning.ai TensorFlow Specialization, you will build natural language processing systems using TensorFlow. You will learn to process text, including tokenizing and representing sentences as vectors, so that they can be input to a neural network.
ACM A.M. Turing Award recipient Jack Dongarra never intended to work with computers. Initially, the Distinguished Professor at the University of Tennessee and founder of the Innovative Computing Laboratory (ICL) thought he would be a high school science teacher. A chance internship at the Argonne National Laboratory kindled a lifelong interest in numerical methods and software--and, in particular, in linear algebra, which powered the development of Dongarra's groundbreaking techniques for optimizing operations on increasingly complex computer architectures. Your career in computing began serendipitously, with a semester-long internship at Argonne National Laboratory. As an undergraduate, I worked on EISPACK, a software package designed to solve eigenvalue problems.
As a young man, Jack Dongarra thought he would probably teach science to high school students. That was his plan when he enrolled at Chicago State College, which had become Chicago State University by the time he graduated in 1972. Over the course of his studies, he began to be fascinated by computers. In his senior year, physics professor Harvey Leff suggested he apply for an internship at nearby Argonne National Laboratory, where he could gain some computing experience. There, Dongarra joined a group developing EISPACK, a software library for calculating eigenvalues, components of linear algebra that are important to performing simulations of chemistry and physics.
The Deep Learning Specialization is a foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. In this Specialization, you will build and train neural network architectures such as Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, Transformers, and learn how to make them better with strategies such as Dropout, BatchNorm, Xavier/He initialization, and more. Get ready to master theoretical concepts and their industry applications using Python and TensorFlow and tackle real-world cases such as speech recognition, music synthesis, chatbots, machine translation, natural language processing, and more. AI is transforming many industries. The Deep Learning Specialization provides a pathway for you to take the definitive step in the world of AI by helping you gain the knowledge and skills to level up your career.
Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. In the coming weeks, students around the nation will hear their names read aloud, walk across a platform and move their tassels to signify graduation from high school or college. After years of working toward receiving their diploma or degree, they are now off to start a new adventure in their lives. And, for others, there may be the apprehension of not knowing what is next. As a college president, here are five pieces of advice I have for graduating seniors.
As the metaverse industry is expected to be an $800 billion market by 2024, we continue to learn new ways this immersive, virtual environment might better enable us to connect with each other from anywhere in the world. This comes at a time when many are already participating in and benefitting from virtual activities that otherwise would not be possible due to constraints of distance, time or cost. In enabling new opportunities for virtual rather than in-person instruction, the metaverse has the power to transform access to education and the way we learn. The types of education that the metaverse can accommodate are varied, from school-based interactive learning and workplace training to professional accreditation. In so many ways, the metaverse is offering new chances for people to learn what they want by mitigating obstacles of accessibility.
Artificial Intelligence (AI) is a fast-growing and evolving field, and data scientists with AI skills are in high demand. The field requires broad training involving principles of computer science, cognitive psychology, and engineering. If you want to grow your data scientist career and capitalize on the demand for the role, you might consider getting a graduate degree in AI. U.S. News & World Report ranks the best AI graduate programs at computer science schools based on surveys sent to academic officials in fall 2021 and early 2022. Here are the top 10 programs that made the list as having the best AI graduate programs in the US.