This article was updated after publishing the results of our survey of 20 prominent data scientists, in which we asked them, amongst other things, what books had helped them grow the most in their career. In the past weeks, we asked successful data scientists in different industries what books they believe are the best to learn and master the necessary skills to become a data scientist. The books selected on this list come from their suggestions. Data science, business analytics, and machine learning have become critical to numerous aspects of business, while the data scientist profession keeps soaring as one of the most in-demand and well paid in the tech industry. The books reviewed in this article have all received positive feedback from their readers, and they cover a wide range of skills and aspects that a successful data scientist has to master in their career, including statistics, data mining, machine learning, Python, business analytics, and more.

Data science and machine learning are two concepts that fall within the field of technology and using data to further how we create and innovate products, services, infrastructural systems, and more. Both correspond with career paths that are in-demand and high-earning. The two relate to each other in a similar way that squares are rectangles, but rectangles are not squares. Data science is the all-encompassing rectangle, while machine learning is a square that is its own entity. They are both often used by data scientists in their work and are rapidly being adopted by nearly every industry.

When "virtual" became the standard medium in early 2020 for business communications from board meetings to office happy hours, companies like Zoom found themselves hot in demand. They also became prime targets for the next big cyberattack. In the case of Zoom, hackers succeeded in April 2020, with a large data breach that exposed an estimated 500,000 user passwords. This breach, along with the thousands of daily reported cyber attacks in that year show that of the major threats facing businesses today, cybercrime nears the top of the list. Due to a combination of factors, including operations that have moved online and sensitive information crossing remote networks, opportunities for cybercrime are rife and the attacks are becoming more advanced and difficult to contain.

The last few years have been a major accelerator for the robotics industry at large, but warehouse robotics may be the biggest winner of all. Stay at home orders fueled adoption in the early days of the pandemic, as some retailers stayed open after being labeled "essential businesses." Even after things began reopening, those roles have remained difficult to fill, leading many firms to look toward robotic help. All the while, Amazon has had a jump on most of the industry, dating back to the company's acquisition of Kiva Systems a decade ago. The competition continues looking for angles to compete with the 800-pound e-commerce gorilla, and robotics startups have flooded the field, promising an edge.

Welcome to our November 2022 monthly digest, where you can catch up with any AIhub stories you may have missed, get the low-down on recent events, and much more. This month, we hear from researchers who've developed an AI system for live music accompaniment and improvisation. Amongst other things, we also find out more about counterfactual explanations for reinforcement learning, planning robust frictional multi-object grasps, and social bias in knowledge graphs. Olga Vechtomova and Gaurav Sahu envisioned and developed a system, LyricJam Sonic, that uses AI to create a real-time generative stream of music based on an artist's own catalogue of studio recordings. The purpose is to inspire the artist with potentially unexpected combinations of sounds.

Whether you're just beginning to work with Artificial Intelligence (AI) or you already have AI experience and are new to Microsoft Azure, this course provides you with everything you need to get started. Artificial Intelligence (AI) empowers amazing new solutions and experiences; and Microsoft Azure provides easy to use services to help you build solutions that seemed like science fiction a short time ago; enabling incredible advances in health care, financial management, environmental protection, and other areas to make a better world for everyone. In this course, you will learn the key AI concepts of machine learning, anomaly detection, computer vision, natural language processing, and conversational AI. You'll see some of the ways that AI can be used and explore the principles of responsible AI that can help you understand some of the challenges facing developers as they try to create ethical AI solutions. This course will help you prepare for Exam AI-900: Microsoft Azure AI Fundamentals.

In the report's'Voice of the Customer' survey, three quarters of respondents said they are attracted to agile fintech competitors as they offer fast, easy-to-use products and superior customer experiences. Conversely, around half said their current banking relationships were neither rewarding nor emotionally connected, and 52% said banking was not'fun'. Banks can collect customer insights to improve the competitiveness of their digital marketing capabilities, especially when combined with artificial intelligence and machine learning. "The formula for growth sounds simple. Customers want to be provided with personalised experiences, regardless of wherever they may be on their own digital journey. The challenge, however, remains in execution," says Nilesh Vaidya, Global Industry Head, Retail Banking and Wealth Management, Capgemini's Financial Services Strategic Business Unit.

Explore 5 best artificial intelligence books for beginners to read in 2023. With all the hype around artificial intelligence – robots, autonomous cars, etc -- it can be easy to assume that AI is not having an impact on our daily lives. In fact, most of us encounter artificial intelligence in some form or another almost every day. As soon as you wake up to check your smartphone and watch another movie recommended by Netflix, AI has quickly slipped into our daily lives. Some of its applications include process automation, predictive analysis, fraud detection, customer experience enhancement, and more.

Most of the channels in this list are not on other lists from other articles. Before I start, I would like to preface this article by saying that most of these channels are not on other lists. Another thing is that while you watch these channels remember to code along and remember that what you are watching is not just a video, it is something to interact with. Currently, Machine and Deep Learning are some of the fastest-growing fields. These two fields require engineers to have skills like Statistics, Mathematics, Data Analysis, and Coding Machine Learning and Deep Learning Models.

Investors and analysts are starting to push beyond the hype about artificial intelligence and ask more questions about AI software companies' near-term growth prospects. Professional service and software providers including Palantir Technologies Inc., C3.ai Inc. and Veritone Inc. market themselves as AI companies with high growth potential, offering services to enhance enterprise analytical capabilities in sectors like cybersecurity and telecommunications. But amid a tech market downturn, these companies are struggling to convince Wall Street they can withstand the pressures of a weakened macroeconomic environment. "We believe chunky data analytics projects are more likely to be put on hold in a weaker growth environment," Goldman Sachs analysts said in a Nov. 8 note following Palantir's third-quarter 2022 earnings call. All three stocks have been hard-hit amid the broader sell-off in tech stocks in 2022, with Palantir and C3.ai both down about 59% year-to-date as of Nov. 23.