文件名称：Machine Learning for Decision Makers-Apress(2017).pdf
文件大小：3.25MB
文件格式：ZIP
更新时间：2021-01-28 14:37:01
Machine Learning ML
Technology is growing quicker than ever. Social media, the Internet of Things, Big Data, mobile devices, cloud computing, and machine learning are changing the way we live and do business. The whole world and everything in it is getting linked. For example, more than three billion Internet, billions of mobile, and billion devices users are linked to each other and have created a web of data and a collaborative communication ecosystem. Machine learning is the next most important movement of innovation, which is guided by developments in computing power and based on the solid foundation of mathematics. Its capability of accumulation of huge sizes of data in the cloud at nominal cost, and laidback access to sophisticated algorithms, is changing everything around us. Machine learning is the most disruptive and influential technology in the recent time and it’s also able to make changes to the complete business ecosystem. Today, almost every enterprise is willing to integrate machine learning into the fabric of commerce in order to succeed. However, until a few years ago, machine learning was out of scope for businesses. The high cost to incorporate machine learning solutions to the business was backed by scarcity of talent availability, infrastructure, and imperfect data. But innovations in the field of storage devices, microprocessing technologies, and availability of tiny networking devices flipped the dynamics and business sentiment. This sparked the Internet of Things, which is flora and fauna of digitally linked devices. Riding on the wave of IOT, new sets of devices, equipment, and products—like mobile phones, toothbrushes, shirts, light bulbs, cars, and so on—can now interact and talk to each other. These devices—along with the connected ecosystem of machines, people, and processes—generate huge volumes of data. Businesses need that data for effective decision making for their growth, customers, and clients. This needs to be smart, intelligent, and relevant in the market forces enterprises to come up with new way to gather, digest, and apply data for useful purposes. Therefore, this data becomes the main enabler of IoT and machine learning. The impact of machine learning, IoT, and Big Data analytics is not limited just to the business; ultimately it can go miles ahead to provide satisfaction to the customer and create new avenues of profit generation that matter most to the business. Machine learning made it possible to generate a complete universe of business applications, products, and capabilities that serve customers and enhance life experiences of the individuals across domains, verticals, and industries. This includes finance, manufacturing, retails, sales, service, marketing, and so on....
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Machine Learning for Decision Makers_Cognitive Computing Fundamentals for Better Decision Making-Apress(2017).pdf