Trading


AI and Blockchain Will Transform Sports Betting for Good Tech Talk

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Bettium is a global decentralized platform enabling users to bet on sporting events against each other, each using big data and established experts to improve forecasts and strategy. Bettium provides direct access to AI, Big Data and powerful analytical tools to help the bet-tor make smart conclusions and smart bets against peers. I started following the blockchain industry in 2015 and immediately recognized the disruptive potential of the technology. This movement has many similarities to the dotcom boom of the 1990s and early 2000s -- a technology that changed the world in ways that could not even be conceived 10 years earlier. Similar to the dotcom, we are seeing explosive growth that will likely be followed by a temporary downturn, eventually shifting to an upturn again, synthesizing the blockchain industry into a stable market as the technology becomes firmly integrated into everyday lives.


Classification-Based Machine Learning for Finance

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Finally, a comprehensive hands-on machine learning course with specific focus on classification based models for the investment community and passionate investors. In the past few years, there has been a massive adoption and growth in the use of data science, artificial intelligence and machine learning to find alpha. However, information on and application of machine learning to investment are scarce. This course has been designed to address that. It is meant to spark your creative juices and get you started in this space.


Validea Joel Greenblatt Strategy Daily Upgrade Report - 5/26/2018

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The following are today's upgrades for Validea's Earnings Yield Investor model based on the published strategy of Joel Greenblatt . This value model looks for companies with high return on capital and earnings yields. DXC TECHNOLOGY CO ( DXC) is a large-cap growth stock in the Software & Programming industry. The rating according to our strategy based on Joel Greenblatt changed from 30% to 90% based on the firm's underlying fundamentals and the stock's valuation. A score of 80% or above typically indicates that the strategy has some interest in the stock and a score above 90% typically indicates strong interest.


Stock Technical Analysis with Python Udemy

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It explores main concepts from basic to expert level which can help you achieve better grades, develop your academic career, apply your knowledge at work or do research as experienced investor. Learning stock technical analysis is indispensable for finance careers in areas such as equity research and equity trading. It is also essential for academic careers in quantitative finance. And it is necessary for experienced investors stock technical trading research and development. But as learning curve can become steep as complexity grows, this course helps by leading you step by step using S&P 500 Index ETF prices historical data for back-testing to achieve greater effectiveness.


CryptoDataDownload.com - Free historical time series data - Excellent for Backtesting strategies, statistical analysis and machine learning

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Check out CryptoDataDownload's Statistical Analysis section for updates as we build this out! These measures rely on math and are used for both risk management and finding market inefficiencies or opportunities. There are many resources available, but CryptoDataDownload recommends you visit PythonProgramming.net


Qualcomm will gain more than its rivals do, as artificial intelligence grows at the 'edge'

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The artificial intelligence market, though still in its infancy, is expected to be the primary driver for many technology companies in the next decade. Shifts in how artificial intelligence (AI) is applied to computing and how consumers will interact with it are moving the emphasis from the server room to the devices in our pockets, a change that could benefit mobile-first players like Qualcomm QCOM, 0.90% In the current vision of AI, computing is associated with the cloud, large clusters of servers computing constantly in data centers. This model is led by Nvidia NVDA, 0.30% a company that CEO Jensen Huang has deftly maneuvered into the pole position for large-scale machine learning. There are fast followers to watch, though, including both Intel INTC, 0.71% a stalwart in the data-center space, and Google GOOG, -0.25% building its own chips for AI processing. This need for server-based artificial intelligence won't be going away as it is responsible for training the complex models and data sets required for AI to be applied on consumer and commercial devices.


What Is the US Banks' AI Strategy?

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Artificial intelligence and machine learning saw a significant spike of attention in the past few years – whether it's through partnerships, acquisitions, or in-house developments. The largest financial institutions in the US have been involved in one way or another in bringing artificial intelligence into operations and customer-facing functions. A recent study of 34 major banks across several geographies (US, EU, Singapore, Africa, Australia, India) by MEDICI Team found that 27 out of these 34 banks have implemented AI in their front-office functions in form of a chatbot, virtual assistant, and digital advisor. Some of the most prominent banks in this space across regions are Bank of America, OCBC, ABN Amro, YES BANK, etc. While front-office applications have certainly seen a higher intensity, scope, and adoption, the AI strategy in the US banking industry, in reality, is far more diverse.


Artificial Intelligence (AI) in Agriculture Market will be grow in the upcoming year with players:Connecterra, Vision Robotics – satPRnews

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The Research report presents a complete assessment of the market and contains Future trend, Current Growth Factors, attentive opinions, facts, historical data, and statistically supported and industry validated market data. The study is segmented by products type, application/end-users. The research study provides estimates for Global Artificial Intelligence (AI) in Agriculture Forecast till 2023. If you are involved in the Artificial Intelligence (AI) in Agriculture industry or intend to be, then this study will provide you comprehensive outlook. It's vital you keep your market knowledge up to date segmented by Applications Precision Farming, Drone Analytics, Agriculture Robots, Livestock Monitoring & Other, Product Types such as [Machine Learning, Computer Vision & Predictive Analytics] and some major players in the industry.


IBM Begins Introducing AI-Enabled Scanner for Global Trade

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The innovation engine of the IBM corporation is rolling out the technology with one of its first clients, GIA (Gemological Institute of America) -- an independent non-profit that protects gem and jewelry customers, to help them evaluate and grade diamonds. Objects and substances that are worn, eaten or used every day will also be open to the scrutiny of the IBM Crypto Anchor Verifier software as it can validate a product's unique optical patterns, sometimes undetectable by the human eye, that differentiates them from each other. Within the next five years, IBM has stated that the digital ledger, blockchain, and cryptographic anchors, which are computers that are smaller than a grain of salt, will be able to prove the authenticity of a product. IBM has stated that, within the next five years, cryptographic anchors and blockchain digital ledger for recording transactions will ensure a product's authenticity -- from its point of origin to the hands of the customer. In a blog post, IBM stated: "By collaborating with GIA, we're taking this research outside of the lab and into a real-world setting.


Artificial Intelligence (AI) in Retail Market to hit $8bn by 2024

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Artificial Intelligence (AI) in Retail Market size is set to exceed USD 8 billion by 2024; according to a new research report by Global Market Insights, Inc. The AI in retail market is driven by the increasing investments in it across the globe. The growing investment in the technology is attributed to the wide applications of the AI technology along with advanced analytics, machine learning. AI is set to unleash the next phase of the digital disruption and the market participants are preparing themselves for it. The investment in the technology is growing rapidly, dominated by the tech giants such as Google, Microsoft, IBM, AWS, and Baidu.