Collaborating Authors

Machine Learning Applications: Machine Learning in the Enterprise


The good news for enterprises is that all the data they have been saving for years can now be turned into a competitive advantage and lead to the accomplishment of strategic goals. Revenue and senior management teams are concentrating on how they can capitalize on machine learnings' core strengths to transform the strategic vision of their businesses into a reality. These teams are focusing on business outcomes first and are looking for machine learning to accelerate and simplify, determining which factors most influence buying behavior and lead to goals being accomplished. My colleague, Elliot Yama, recently wrote about why it is necessary to leverage machine learning to drive business outcomes. Predicting propensity to buy across channels, making personalized recommendations to customers, forecasting long-term customer loyalty, and anticipating potential revenue and credit risks of buyers are some specific applications of machine learning right now.

Applications and Types of Machine Learning


What are the applications of machine learning? According to Wikipedia: Machine learning (ML) is the study of computer algorithms that improve automatically through experience. It is seen as a subset of artificial intelligence. Machine learning algorithms build a model based on sample data, known as "training data", in order to make predictions or decisions without being explicitly programmed to do so. Machine Learning has opened a new vista of marketing and business process optimization in the retail sector.

Are You Joining The Machine Learning Revolution?


Have you noticed that the better you know someone, the easier it is to communicate with them? When we are particularly close, this can border on the telepathic as we start to anticipate what the other person is going to say and finish their sentences. Unconsciously, our brains are collecting, processing, storing, and recalling a huge range of verbal and nonverbal signals, then translating this learning and familiarity into actions. Of course, we're a long way from understanding – let alone replicating – the infinite complexities of the human brain. But in the simplest of terms, this is how machines can learn to interact with people.

Deep Learning Applications for Enterprise with Skymind's Chris Nicholson -


Episode Summary: In one of our most recent consensus, we took a close look at future trends in artificial intelligence consumer applications, but it's also interesting to see what's happening now in businesses. Chris Nicholson is the CEO of, which offers deep learning applications that integrate with Hadoop and Spark. In this episode, Nicholson sheds light on current trends that he sees across industries and best practices for implementing AI solutions to gain consistent return on investment. Brief Recognition: Chris Nicholson leads Skymind, the commercial support arm of the open-source framework Deeplearning4j. Skymind helps companies in telecommunications, finance, retail and tech build enterprise deep learning applications, notably fraud detection, using data such as text, time series, sound and images.

Angular - Complete Understanding & Learning With A Project


The course is created to learn Angular 12 and the detailed planning needed for creating an Angular application. Which will help you to create applications from scratch & maintainable for increasing the scale of it as well. The course covers the below things. How learning will be simpler & clear with Project? I tried to introduce all concepts by giving first a practical solution & then understanding in depth.