If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Functional programming is a style of programming that is characterized by short functions, lack of statements, and little reliance on variables. You will learn what functional programming is, and how you can apply functional programming in Python. In this video course, we will learn what functional programming is, and how it differs from other programming styles, such as procedural and object-oriented programming. We will also learn why and when functional programming is useful, and why and when it makes programs unnecessarily complex. Then we go on to explore lambda expressions, which are short one-line functions, and are the purest form of functional programming that Python offers.
Prerequisites: No prerequisites, knowledge of some undergraduate level mathematics would help but is not mandatory. Working knowledge of Python would be helpful if you want to run the source code that is provided. Taught by a Stanford-educated, ex-Googler and an IIT, IIM - educated ex-Flipkart lead analyst. This team has decades of practical experience in quant trading, analytics and e-commerce. The course is shy but confident: It is authoritative, drawn from decades of practical experience -but shies away from needlessly complicating stuff.
Python is an object-orientated language that closely resembles the English language which makes it a great language to learn for beginners as well as seasoned professionals. Examples sites that use Python are Instagram, YouTube, Reddit, NASA, IBM, Nokia, etc. Python is one of the most widely used programming languages in the AI field of Artificial Intelligence thanks to its simplicity. It can seamlessly be used with the data structures and other frequently used AI algorithms. This is because it is the ideal language to work with for general purpose tasks. Experienced coders tend to stay more organized and productive when working with Python, as well.
Python is a big deal. More and more beginner programmers are choosing it as their first language to learn, which means its future is more than just bright - it's dazzling. It makes coding faster, easier and fun. When combined with the object oriented programming approach these qualities are further enhanced, which means Python is virtually unstoppable. If you want to future-proof your programming skills, this is exactly what you need to learn.
GreyCampus is a leading provider of online self-learning courses for working professionals. This course is on Python, which is one of the easiest, most effective and most widely-used programming languages of today. Its efficient high-level data structures, simple yet effective approach to object-oriented programming, dynamic typing and elegant syntax, make Python an ideal language for both experts and novices for quick application development. The code is similar to English and doesn't need much technical knowledge to be read & understood. In this online self-learning course, you'll be taken through the very basics of Python assuming zero prior understanding of programming languages.
Let's get started with knowing what exactly a neural network is- A neural network is an abstract concept which is derived from the neurons from our brain. So, before diving further into details let's step back and take a look at what the neurons in our brain do and how do the artificial neural network resemble the natural neurons in our brain. But wait a second, why are we even doing this? Why do we need a neural network? We have come far as a species but we still face a lot of issues which are yet to be solved.
As the amount of data continues to grow at an almost incomprehensible rate, being able to understand and process data is becoming a key differentiator for IT professionals and data-scientists. The scikit-learn library is one of the most popular platforms for everyday Machine Learning and data science because it is built upon Python, a fully featured programming language. This comprehensive 3-in-1 course is your one-stop solution to everything that matters in mastering machine learning algorithms and their implementation. Develop pipelines and process data through manipulation, extraction, and data-cleansing techniques. Learn clean coding techniques which are applicable to any scalable Machine Learning projects.
This article will cover a brief introduction to these topics and show how to implement them, using Google Colaboratory to do automated machine learning on the cloud in Python. Originally, all computing was done on a mainframe. You logged in via a terminal, and connected to a central machine where users simultaneously shared a single large computer. Then, along came microprocessors and the personal computer revolution and everyone got their own machine. Laptops and desktops work fine for routine tasks, but with the recent increase in size of datasets and computing power needed to run machine learning models, taking advantage of cloud resources is a necessity for data science.
Python is a popular general purpose programming language used for both large and small-scale applications. Python's wide-spread adoption is due in part to its large standard library, easy readability and support of multiple paradigms including functional, procedural and object-oriented programming styles.This Course follows pragmatic approach to tackle end-to-end data science project cycle right from extracting data from different types of sources to exposing your machine learning model as API endpoints that can be consumed in a real-world data solution. This course will not only help you to understand various data science related concepts, but also help you to implement the concepts in an industry standard approach by utilizing Python and related libraries. By the end of this course, you will have a solid foundation to handle any data science project and have the knowledge to apply various Python libraries to create your own data science solutions.
This course is a lead-in to deep learning and neural networks - it covers a popular and fundamental technique used in machine learning, data science and statistics: logistic regression. We cover the theory from the ground up: derivation of the solution, and applications to real-world problems. We show you how one might code their own logistic regression module in Python. This course does not require any external materials. Everything needed (Python, and some Python libraries) can be obtained for free.