This tutorial has introduced you to Machine Learning, an area of artificial intelligence that allows machines to learn from data and to perform tasks that would typically require human intelligence. With Machine Learning, machines are able to learn from their experiences, process complex data, and make decisions beyond the capability of a human brain. Examples of this include machines beating human champions in games such as Chess and AlphaGO, which are considered to be very complex. Furthermore, Machine Learning can be used to assist humans in many aspects of life, such as healthcare, transportation, finance, and more. By enabling machines to make decisions more quickly and accurately than a human, Machine Learning can help people to live better lives.
Supervised Learning is used when the data set is relatively small and the labels are clearly defined. It involves training models on labeled data to predict outcomes. Unsupervised Learning is better suited for larger data sets as it does not rely on labeled data and instead discovers patterns in the data. Deep Learning techniques can be used with large data sets for even better performance and results. Neural Networks are powerful tools for complex tasks and applying them can lead to powerful insights. However, these networks have limitations and require careful tuning and understanding of the underlying data. Reinforcement Learning and Deep Reinforcement Learning are also powerful tools for learning from interactions with the environment.
When it comes to the development of machine learning models, it is important to consider the choices of various development languages, IDEs and Platforms. To properly learn and practice each machine learning technique, it is best to take one topic at a time. This allows for a deeper understanding of the subject and allows for the implementation of algorithms using the language of choice. Working through one topic at a time will eventually give the user the width that is required of a Machine Learning expert. It is important to take the time to properly understand each topic before moving on to the next.