Machine Learning frameworks and libraries are the tools that help develop and deploy machine learning models. The most popular ML frameworks are TensorFlow, Keras, and PyTorch. TensorFlow is an end-to-end open-source platform that was created with the goal of improving machine learning. The Google Brain team developed TensorFlow for internal Google use in research and production. TensorFlow has many features, providing extensive, open-source tools to researchers and developers.

Machine learning has become ubiquitous in many industries. Online retailers use machine learning to predict what customers will buy, doctors use it to diagnose illnesses, and marketers use it for targeted advertising. These are just a few examples of how machine learning can be applied to improve our society. The types of machine learning are shown in Figure 1.

Artificial Intelligence (AI) and machine learning (ML) have been hot topics the last few years, and for a good reason. With AI, we can do previously impossible or costly to do things. Artificial intelligence is also benefiting businesses by automating processes, saving time and money, and improving customer experiences. But what every business leader must know about AI and ML? AI is already playing an important role in our lives, but it is just the beginning. It has the potential to change how we work, teach, live and interact with others.

Many AI techniques are being used in organizations, and AI will continue to get sophisticated in the third wave of AI. In the Fourth Industrial Age, human creativity, AI at scale, and Emotion AI will be dominant forces that will shape the digital organizations of the future. What is the Third Wave of AI? In the first wave, artificial intelligence (AI) systems followed clear rules and were directed at individual applications of the algorithms to cover every eventuality. The second wave was the introduction of deep learning and reinforcement learning systems that mapped inputs to outputs to solve a certain type of problem.