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10 Books on AI Machine Learning You Shouldn't Miss Reading


"If you program a machine, you know what it's capable of. If the machine is programming itself, who knows what it might do?" ― Garry Kasparov Artificial Intelligence is a complex subject. However, reading and acquiring knowledge through books written on Artificial Intelligence, Machine Learning, Data Science and other related topics can help technology enthusiasts to a great extent. Here is a list of ten books on AI and Machine Learning that provide the information on basics of technology, its present, the future paradigm and the most rabid fictionalized set-ups that are expected to arrive in the coming future. We have rated the books on a scale of 1-5, considering their depth, research, uniqueness, reader's review, and the AiThority News Quotient.

AiThority Interview With Ryan Duguid, Chief Evangelist, Nintex Questions


The thing I like the most is when I don't even know that I'm interacting with intelligent technologies because the people providing them have done such a great job of making them a natural part of my work flow. Whether it's voice recognition, advanced image analysis, sentiment analysis, or document processing, I love having it baked in to the products and applications that I use every day. It can be as simple as a conversation with Alexa to understand the weather and traffic for the day, or getting recommendations for articles I should be reading or presentations I should be watching. It can be as sophisticated as gaining insights into how I can better manage my team by analyzing how they're thinking and feeling through the employee engagement platform which we use. Either way, I'm looking for the little ways to be more efficient and effective.

AiThority Interview with Malina Platon, Managing Director at UiPath


I have years of experience in the enterprise software space, starting in my early years as a Customer Representative for WebHelp before expanding into market development for Intel which saw me take on a more Business Development role. My roles in companies such as Intel, Softwin and ABC Data were very Business Development-orientated which meant that I had to become an expert in the technology and in understanding how that technology could solve the problems that my customers faced. It also meant that I had to build and maintain relationships, skills that have served me very well in my recent role at UiPath. Throughout my career I saw how good quality enterprise technologies can really help drive a company's competitiveness and productivity, so UiPath was a natural fit for me when I joined them in 2016. I have helped drive UiPath's expansion into ASEAN, from setting up offices in Thailand, Singapore, Malaysia, Indonesia, the Philippines, and South Korea, to hiring staff and providing strategic oversight of operations.

AiThority Interview with Robin Bordoli, President at RollWorks


Before joining RollWorks, I was the CEO of Figure Eight, the leading training data platform for Machine Learning teams. Figure Eight sold its platform into the automotive, financial services, media and entertainment, retail, and technology industries supporting both Natural Language Processing (NLP) and Computer Vision use cases. Thus, I have a broad and deep understanding of the current state of AI and Machine Learning in the real world. Beyond Figure Eight, my experience with Computer Vision goes back almost 30 years when I was working on primitive object identification for robots in manufacturing plants when I was studying engineering at Cambridge University. I have a 25-year history with AI and Machine Learning.

AiThority Interview With Hitesh Sheth, CEO at Vectra


My passion for security came to the forefront when I ran the Security business at Juniper. Given this confluence of factors, the opportunity to apply Artificial Intelligence (AI) to dramatically innovate how we could detect and respond to advanced attacks (the new norm), created an incredible opportunity to build a next-generation security company. Which directly led to the creation of Vectra. Digital Transformation can become a task rife with complexities and it is no surprise that security risks become a byproduct of that. Effective Network Detection and Response (NDR) provides visibility that simplifies complexity, replacing it with the confidence that a customer's security capabilities will enable, not inhibit, their journey – legacy methods disproportionately focused on prevention are brittle and frankly designed in such a way that makes this journey needlessly costly and difficult.