Viyogi Learning

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REINFORCEMENT LEARNING Reinforcement learning  ( RL ) is an area of  machine learning  concerned with how  software agents  ought to take  actions  in an environment in order to maximize the notion of cumulative reward. Reinforcement learning is one of three basic machine learning paradigms, alongside  supervised learning  and  unsupervised learning . without some feedback about what is good and what is bad, the agent will have no grounds for deciding which move to make.   The agent needs to know that something good has happened when it (accidentally) checkmates the opponent, and that something bad has happened when it is checkmated-or vice versa, if the game is suicide chess. This kind of feedback is called a reinforcement or reward. Rewards served to define optimal policies in Markov decision processes (MDPs). An optimal policy is a policy that maximizes the expected total reward. The task of reinforcement learn...

History of Artificial Intelligence

Introduction to Data Data is basically useful information about anything and of anybody. Data is commonly known as big data. this could be anything like the rating for a movie by a user, purchasing history, searching history, preferences of a user, likes and dislikes of a user, etc. in the field of Data Science, the Data/Big Data is classified into two categories:- Qualitative Data Quantitative Data     Qualitative Data it deals with characteristics and descriptions that can't be measured easily but can be observed subjectively.  Qualitative data is a type of data that describes the information. It is investigative and also often open-ended, allowing respondents to fully express themselves. it is also known as categorical data.  this data type isn’t necessarily measured using numbers but rather categorized based on properties, attributes, labels, and other identifiers. example:- qualifications,sex,name, etc. this data is also classified in...

                              Automating tasks  you can automate simple tasks such as the following : Moving and renaming thousands of files and sorting them into folders Filling out online forms, no typing required Downloading files or copy text from a website whenever it updates Having your computer text you custom notifications Updating or formatting Excel spreadsheets Checking your email and sending out prewritten responses These tasks are simple but time-consuming for humans, and they’re often so trivial or specific that there’s no ready-made software to perform them. Armed with a little bit of programming knowledge, you can have your computer does these tasks for you.            Automate boring stuff Download

                      Introduction To Regular Expressions A  regular expression  is a special sequence of characters that helps you match or find other strings or sets of strings, using a specialized syntax held in a pattern. Regular expressions are widely used in the UNIX world. example:- Searching date and time in the datasheet, textbook, etc. Regular expressions can contain both special and ordinary characters. they simply match themselves. these are generally made by using meta-characters and repetition qualifiers. Meta Characters are shown below:- Repetition Qualifiers are shown below:- Note:- these are used in text mining and text analysis, etc.

                                 Advantages Of Machine Learning To wrap up our discussion of the microlending example, we list some of the most prominent advantages to using a machine-learning system, as compared to the most common alternatives of manual analysis, hardcoded business rules, and simple statistical models. The five advantages of machine learning are as follows: Accurate:-  ML uses data to discover the optimal decision-making engine for your problem. As you collect more data, accuracy can increase automatically. Automated:-  As answers are validated or discarded, the ML model can learn new patterns automatically. This allows users to embed ML directly into an automated workflow. Fast:-  ML can generate answers in a matter of milliseconds as new data streams in, allowing systems to react in real-time. Customizable:-  Many data-driven problems can ...