People who want to learn about machine learning and deep learning will work on five real-world projects. Are you ready to start your path to becoming a Data Scientist or ML Engineer? This comprehensive course will be your guide to learning how to use the power of Python to analyze data, create beautiful visualizations, and use powerful machine learning algorithms! Data Scientist has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $120,000 in the United States according to Indeed! Data Science is a rewarding career that allows you to solve some of the world's most interesting problems!

Gain a competitive edge in the world of Computer Vision through this course by learning how to do Smart Data Extraction from Pdf and Images. Gain a competitive edge in the world of Computer Vision through this course by learning how to do Smart Data Extraction from Pdf and Images. The technology landscape of world has brought in cognitive skills at the forefront where major emphasis is on intelligent data extraction. This becomes more complex due to the huge variety of input documents such as pdf document with structured data, scanned pdf document and word document. This course aims to solve this challenging problem by helping you to understand these various formats and then empower you to do smart data extraction using Python, Pandas, OCR, Tesseract, PyTesseract, OpenCV, Spacy and NER concepts.

Understand how to overcome RPA Implementation Challenges · Have a good grasp on how to Prepare and Launch a RPA project · Identify how to select the right process ... Robotics Process Automation(RPA) is changing the way we work and has become an integral element for any company who is thinking about digital transformation. This market is growing at a rapid pace and professionals need to evolve to become a part of this intelligent digital workforce. Do you want to be in the smart crowd and take the RPA Path? Then, this course is for you as it aims to answer the Why, What and How of RPA Implementation by adopting a step-by-step approach. We will teach you the essentials of RPA, explain how to overcome RPA Challenges like Process Analysis, Process Identification, Building an RPA team for RPA Managers, Business Case Issues and ROI Analysis through use cases.

In this complete deep reinforcement learning course you will learn a repeatable framework for reading and implementing deep reinforcement learning research ... In this complete deep reinforcement learning course you will learn a repeatable framework for reading and implementing deep reinforcement learning research papers. You will read the original papers that introduced the Deep Q learning, Double Deep Q learning, and Dueling Deep Q learning algorithms. You will then learn how to implement these in pythonic and concise PyTorch code, that can be extended to include any future deep Q learning algorithms. These algorithms will be used to solve a variety of environments from the Open AI gym's Atari library, including Pong, Breakout, and Bankheist. You will learn the key to making these Deep Q Learning algorithms work, which is how to modify the Open AI Gym's Atari library to meet the specifications of the original Deep Q Learning papers.

I will recommend this class to any one looking towards Data Science" "This course so far is breaking down the content into smart bite-size pieces and the professor explains everything patiently and gives just enough background so that I do not feel lost." "This course is really good for me. it is easy to understand and it covers a wide range of NLP topics from the basics, machine learning to Deep Learning. The codes used is practical and useful. I definitely satisfy with the content and surely recommend to everyone who is interested in Natural Language Processing"

The word community has become a buzzword across the globe. Businesses have realized the power of community-led growth and are heavily invested in building and continuously giving to the audience. At Analytics Vidhya, the community has been at the forefront since its inception with aim of building the best AI ML ecosystem any company can offer. With a Leading community knowledge portal, our ecosystem is magnifying at a 3x speed. Keeping the community in mind, we are happy to announce that we have launched a webinar series: The DataHour.

This is a Free to Audit course on Coursera. That means you can access the course material free of cost but for the certificate, you have to pay. In this course, you will understand the basics of computer vision and learn color, light, and image formation; early, mid-level, and high-level vision; and mathematics essential for computer vision. Throughout this course, you will apply mathematical techniques to complete computer vision tasks. You will get a free license to install MATLAB for the duration of the course is available from MathWorks.

How to start Machine Learning journey: A step-by-step Guidance · Step 0: Learn the basics of Python · Step 1: Try to find answers to some basic questions related ... What does Siri, Alexa and Google Play have in common? How is Capital One and Paypal able to instantly detect fraudulent transfers? How is Google Photos able to identify faces in photos? How is Youtube able to make wickedly smart suggested videos? Or Amazon know what you want before you do?

Ready to spin up a virtual GPU instance and smash through petabytes of data? Want to add'Machine Learning' to your LinkedIn profile? Before you embark on your journey, there are some high-level theory and statistical principles to weave through first. Please feel welcome to join this introductory course by buying a copy, or sending a free sample to your chosen device.

Recent advances in artificial intelligence, specifically machine learning, contributed positively to enhancing the autonomous systems industry, along with introducing social, technical, legal and ethical challenges to make them trustworthy. Although Trustworthy Autonomous Systems (TAS) is an established and growing research direction that has been discussed in multiple disciplines, e.g., Artificial Intelligence, Human-Computer Interaction, Law, and Psychology. The impact of TAS on education curricula and required skills for future TAS engineers has rarely been discussed in the literature. This study brings together the collective insights from a number of TAS leading experts to highlight significant challenges for curriculum design and potential TAS required skills posed by the rapid emergence of TAS. Our analysis is of interest not only to the TAS education community but also to other researchers, as it offers ways to guide future research toward operationalising TAS education.