Rather than letting players port weapons or powers between games, non-fungible tokens will more likely serve as building blocks for new games and virtual worlds. One of the most enduring legends in the cryptocurrency industry is that Vitalik Buterin started Ethereum because his warlock got nerfed. "I happily played World of Warcraft during 2007-2010," Vitalik wrote in one version of the story. "But one day Blizzard removed the damage component from my beloved warlock's Siphon Life spell. I cried myself to sleep, and on that day I realized what horrors centralized services can bring. I soon decided to quit."
This course aims at providing an introductory and broad overview of the field of ML with the focus on applications on Finance. Supervised Machine Learning methods are used in the capstone project to predict bank closures. Simultaneously, while this course can be taken as a separate course, it serves as a preview of topics that are covered in more details in subsequent modules of the specialization Machine Learning and Reinforcement Learning in Finance. The goal of Guided Tour of Machine Learning in Finance is to get a sense of what Machine Learning is, what it is for and in how many different financial problems it can be applied to. The course is designed for three categories of students: Practitioners working at financial institutions such as banks, asset management firms or hedge funds Individuals interested in applications of ML for personal day trading Current full-time students pursuing a degree in Finance, Statistics, Computer Science, Mathematics, Physics, Engineering or other related disciplines who want to learn about practical applications of ML in Finance Experience with Python (including numpy, pandas, and IPython/Jupyter notebooks), linear algebra, basic probability theory and basic calculus is necessary to complete assignments in this course.
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Earlier this month, DeepMind presented a new "generalist" AI model called Gato. The model can play the video game Atari, caption images, chat, and stack blocks with a real robot arm, the Alphabet-owned AI lab announced. All in all, Gato can do hundreds of different tasks. But while Gato is undeniably fascinating, in the week since its release some researchers have got a bit carried away. One of DeepMind's top researchers and a coauthor of the Gato paper, Nando de Freitas, couldn't contain his excitement.
How are you evolving your skills for the future of work? This is one of the most pertinent questions workers are asking themselves. However, the answer is constantly changing. With every new technology, innovation, regulation, and system, the most in-demand skills shift. The capabilities that employers are looking for today are no longer the capabilities of last year, and in many industries this has created a significant skills gap.
This course will enable you mastering machine-learning approaches in the area of investment management. It has been designed by two thought leaders in their field, Lionel Martellini from EDHEC-Risk Institute and John Mulvey from Princeton University. Starting from the basics, they will help you build practical skills to understand data science so you can make the best portfolio decisions. The course will start with an introduction to the fundamentals of machine learning, followed by an in-depth discussion of the application of these techniques to portfolio management decisions, including the design of more robust factor models, the construction of portfolios with improved diversification benefits, and the implementation of more efficient risk management models. We have designed a 3-step learning process: first, we will introduce a meaningful investment problem and see how this problem can be addressed using statistical techniques.
Listen to this episode on Anchor FM. Stefan has been a partner in an investment firm where he assisted in building data infrastructure and predictive analytics practice. He accomplished this when data science was only beginning to be taken seriously in the investment industry. You won't want to miss this opportunity to learn from Stefan's experiences. Machines learning from data will continually improve in achieving performance measures.
"Quality is never an accident. It is always the result of intelligent effort" – John Ruskin The adoption of artificial intelligence (AI) is gathering pace. And with a significant level of adoption in emerging markets, the trend has seen an increase in almost every industry, encompassing a range of business sectors from production, through marketing and sales to HR and risk management. Alongside this trend, companies are broadening their focus to include stakeholders beyond their shareholders. This can be attributed to a variety of factors.
The stock market is currently on the roughest losing streak since the start of the pandemic in 2020. The broad S&P 500 index is down 19% from its all-time high, putting it within a whisker of bear market territory. But the tech-centric Nasdaq-100 index is already there, with a loss of 28.3% since November 2021. While the investment picture might be nerve-wracking for many investors, history suggests down markets always eventually recover, so this might actually be a great time to put some money to work. Here's one fast-growing stock leveraging advanced technology, and it's worth considering because it's trading at an 88.9% discount to its all-time high, despite the company being highly profitable.