Build a Portfolio of Machine Learning Projects, and take your Career to the Next Level. This career-ready Masterclass is designed to help you gain hands-on and in-depth exposure to the domain of Data Science by adopting the learn by doing approach. And the best way to land your dream job is to build a portfolio of projects. And the best platform for a Data Scientist is Kaggle! Over the years, Kaggle has become the most popular community for Data Scientists.

Artificial neural networks are considered to be the most efficient Machine Learning techniques nowadays, with companies the likes of Google, IBM and Microsoft applying them in a myriad of ways. You've probably heard about self-driving cars or applications that create new songs, poems, images and even entire movie scripts! The interesting thing about this is that most of these were built using neural networks. Neural networks have been used for a while, but with the rise of Deep Learning, they came back stronger than ever and now are seen as the most advanced technology for data analysis. One of the biggest problems that I've seen in students that start learning about neural networks is the lack of easily understandable content.

Generate Income and make a living with Day Trading / Algorithmic Trading. This unique course provides the skills, knowledge, and techniques required to (realistically!) answer that question. The course uses rigorous quantitative methods and is 100% data-driven (Python coding required!).

Python based YOLO Object Detection using Pre-trained Dataset Models as well as Custom Trained Dataset Models. Python based YOLO Object Detection using Pre-trained Dataset Models as well as Custom Trained Dataset Models. This is the fourth course from my Computer Vision series. As you know Object Detection is the most used applications of Computer Vision, in which the computer will be able to recognize and classify objects inside an image. This course is equally divided into two halves.

This course will help you master the basic concepts of Python 3.9.6 within just 2 hours. The Basics of Python course covers, the concepts of Python Programming in 2 hours, and then you'll be creating your own applications, working with coding quizzes and challenges to excel what you learned. Python is one of the world's top 3 programming languages, and it's the most used language by businesses and enterprises. Python developers make over $150,000 a year and you can create desktop applications, websites and work with Machine Learning Algorithms with Python. The important thing that makes Python a great programming language is its easy syntax and simplicity.

This course covers concepts & case studies for executives and senior managers to better understand AI. If you don't do something about AI, you will be left behind or disrupted into extinction – this is a message that executives, Managers, Team Leaders and CXOs often hear, especially in the last year or so from consultants, vendors, industry experts or the IT organization. Today, companies are faced with some compelling new choices, like robotic process automation (RPA), artificial intelligence (AI), machine learning (ML), blockchain and Industrial Internet of Things (IIoT), to name a few. Corporate Leaders have the daunting task of deciphering what these buzzwords mean, understanding what is relevant to their business and determining which technology to invest. It's important that Leaders have a foundational knowledge of digital transformation because they will rely on digital business to make their numbers.

NON TECHNICAL COURSE specifically created for AI/ML/DL Aspirants, gives insight about Road map to A.I NON TECHNICAL COURSE specifically created for AI/ML/DL Aspirants, gives insight about Road map to A.I Each video is created with real time scenario examples in simple language. So that anyone without programming knowledge can understand in depth about Artificial Intelligence and Machine Learning. The contents were prepared based on maximum queries searched in google or posted in AI forum. At the end of this course you will get clear clarity on how much effort needed to start your career in Artificial Intelligence or Machine Learning Projects. So I will be updating the captions manually as soon as possible.

With the popularity and success of our first Introduction to Embedded Machine Learning course, we decided to launch another! We listened to feedback from students, engineers, and industry leaders about which areas in tinyML were most interesting and useful. One topic stood above the rest: vision. Shawn Hymel returns as the main instructor, and we teamed up with OpenMV, Seeed Studio, and the tinyML Foundation to create a new course: Computer Vision with Embedded Machine Learning. The course covers important concepts in computer vision, including how digital images are constructed, stored, and manipulated.

Data engineers are inquisitive, competent problem solvers who enjoy both data and creating helpful things for people. In any case, data engineers, along with data scientists and analysts, are part of a squad that converts raw data into information that gives their companies a competitive advantage. In this article, you will learn about the difference between data engineer and data scientist along with why you should choose data engineer over data scientist. A data engineer is in charge of establishing and maintaining the data architecture and infrastructure that underpins an organization's IT systems and environments. Programming, data storage, database management, and system implementation are all skills that data engineers must have.

Rachel earned her math PhD at Duke University. She is a popular writer and keynote speaker, on topics of data ethics, AI accessibility, and bias in machine learning. Her writing has been read by nearly a million people; has been translated into Chinese, Spanish, Korean, & Portuguese; and has made the front page of Hacker News 9x.