Machine Learning and Sumi Chatbot

10 days may not seem like a lot of time, but with proper self-discipline and time-management, 10 days can provide enough time to gain a survey of the basic of machine learning, and even allow a new practitioner to apply some of these skills to their own project. 10 days? Hm, that’s definitely a challenging task :). However, I think that 10 days is also definitely a time frame where you can get a pretty good overview of machine learning field and maybe get started to apply some techniques to your problems. After reading an introduction to the 3 different subfields (supervised learning, unsupervised learning, and reinforcement learning). I would probably spend the time on simple (yet useful) algorithms that are representative of these fields (and maybe save reinforcement learning for later). E.g., Simple linear regression and Ridge Regression for regression analysis, logistic regression and k-nearest neighbors for classification, and k-means and hierarchical clustering for clusteri

Deep learning is an aspect of artificial intelligence (AI) that is concerned with emulating the learning approach that human beings use to gain certain types of knowledge. At its simplest, deep learning can be thought of as a way to automate predictive analytics. While traditional machine learning algorithms are linear, deep learning algorithms are stacked in a hierarchy of increasing complexity and abstraction. To understand deep learning, imagine a toddler whose first word is “dog.” The toddler learns what is (and what is not) a dog by pointing to objects and saying the word “dog.” The parent says “Yes, that is a dog” or “No, that is not a dog.” As the toddler continues to point to objects, he becomes more aware of the features that all dogs possess. What the toddler does, without knowing it, is to clarify a complex abstraction (the concept of dog) by building a hierarchy in which each level of abstraction is created with knowledge that was gained from the preceding layer of the

  Machine learning is a type of artificial intelligence (AI) that provides computers with the ability to learn without being explicitly programmed. Machine learning focuses on the development of computer programs that can change when exposed to new data. The process of machine learning is similar to that of data mining. Both systems search through data to look for patterns. However, instead of extracting data for human comprehension -- as is the case in data mining applications -- machine learning uses that data to detect patterns in data and adjust program actions accordingly. Machine learning algorithms are often categorized as being supervised or unsupervized. Supervised algorithms can apply what has been learned in the past to new data. Unsupervised algorithms can draw inferences from datasets. Facebook's News Feed uses machine learning to personalize each member's feed. If a member frequently stops scrolling in order to read or "like" a particular friend&#

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