​This course on AI will give all the basics key concepts and intuition training to get you quickly up to speed with all things related to artificial intelligence.
 
If you are new around this industry and want to start from scratch about artificial intelligence then you have come to the right place.

You will learn

• How to start building Artificial Intelligence projects with no previous coding experience using Python only
• How to merge AI with OpenAI Gym to learn and grow your knowledge about AI as effectively as possible
• How to optimize your AI search to reach its maximum potential in the real world

 
Here is what you will get in this particular course:

1. Complete beginner to expert Artificial Intelligence skill operator – Learn to code self-improving AI for a range of purposes. In fact, we code together with you.

2. Code templates – there are various templates that are available over the internet you’ll get downloadable Python code and templates for every AI you build in this particular course, with in depth explanation of each code. This makes building truly unique AI as simple as changing a few lines of code it’s all about unleashing your imagination, then potential is unlimited.

3. Intuition Tutorials –we believe in developing a deep understanding for not only what you’re doing, but why you’re doing it. Most of the courses simply bombard you with dense theory which is very hard to understand and difficult implement

4. Real-world solutions – Each module comprises of varying structures and different difficulty levels, means you’ll be skilled enough to build AI adaptable programs to any situation in real life.

5. In-course support – We’re fully committed to making this the most accessible and results-driven AI course with 24/7 in course support with our faculty members. We are always there when you need our help. That’s why we’ve put together a team of professional Data Scientists to support you in your journey to master artificial intelligence

In this course, you’ll work with more complex environments, specifically provided by the OpenAI Gym: CartPole Mountain Car Atari games to train effective learning agents so you’ll need new techniques. It’s all about the application of neural networks to reinforcement learning and deep learning.

We’ve seen that reinforcement learning is an entirely different kind of machine learning than supervised and unsupervised learning.Supervised and unsupervised machine learning algorithms are for making predictions about data and analyzing, while reinforcement learning is about training an agent to interact with an environment and maximize its reward. Deep reinforcement learning and AI has a lot of potentials also carries huge risk.

One main principle of training reinforcement learning agents is that there are unintended consequences when training an AI. AI’s don’t think like humans, they come up with novel and non-intuitive solutions to reach their goals; often in ways that surprise domain experts.One of the great things about OpenAI is that they have a platform called the OpenAI Gym (heavy use of in this course). In order to train their reinforcement learning agents in the standard environments, it allows everyone and everywhere in this world.

Requirements-Basics of reinforcement learning, Dynamic Programming, TD Learning,Monte Carlo,MDPs; Knowledge of Calculus and probability(Undergraduate level); Experience in building models in machine learningPython and Numpy; Know how to build a feedforward, recurrent neural network using Theano and Tensorflow; convolutional.

About this book is a comprehensive guide towards step into the amazing world of intelligent apps using the world of Artificial Intelligence, this book will help you create your own applications work through simple and comprehensive examples that will get you up and helps you with Artificial Intelligence .
    
This book is for developers particularly coding in python language who want to build real-world Artificial Intelligence applications. Being familiar with Python would be very useful to play around with the codes. It will also be very useful for experienced Python programmers who are looking to use AI techniques in their existing technological stacks.
 
 
You will learn about different regression techniques, classification and understand the core concept of clustering and how to use it to automatically segment data. You will learn how to build an intelligent recommender system, Understand logic behind its programming and how to implement it in building automatic speech recognition systems. Understand the basics of heuristic search and genetic programming Develop games using AI, Learn working of reinforcement learning, discover how to build intelligent applications centered on, text, images and time series data see how to build applications based on deep learning algorithms In detail.

Move on to designing AI solutions in a simple manner rather than get confused by complex techniques and architecture with the help of this amazing book on Artificial intelligence with the help of easy to understand examples. This comprehensive guide on AI will be a starter kit for you to develop applications based on AI and Machine Learning.

Understood the fundamentals of AI and worked through a number of case studies that will help you develop your business vision with this book.
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Artificial Intelligence is becoming increasingly relevant and has various applications in the modern world. By harnessing the power of algorithms, you can create apps which interact with the world around you based on the input feed; you can build intelligent recommender systems, automatic speech recognition systems and much more.
Starting with basics of Artificial Intelligence you'll move on to learn how to develop building blocks using data mining techniques. Learn how to make informed decisions, and how to apply them to real-world scenarios. This book covers nearly all range of topics including predictive analytics and deep learning with suitable the examples.
 
What you will learn
•             Use adaptive thinking and modern knowledge to solve real-life AI case studies and problems
•             Acquire advanced AI, deep learning and machine learning designing skills
•             Learn about quantum computing, cognitive NLP chatbots, IoT and blockchain technology
•             Understand future AI solutions and develop skills to adapt them quickly
•             Develop out-of-the-box thinking to face any challenge related to present market senerios

​Hands-On Machine Learning with Scikit-Learn and TensorFlow is a series of Deep Learning breakthroughs that have boosted the field of Artificial Intelligence and machine learning over the last few decades. Now that machine learning is flroushing, even programmers who know close to nothing about this modern computer technology can use simple, efficient tools and existing language knowledge to implement programs capable of learning from existing data.
 
This practical book shows you how          
Develop application on Artificial Intelligence using different approaches and  examples, with minimal theory, and two production-ready Python frameworks— TensorFlow and scikit-learn —author Sir Aurélien Géron develops an intuitive understanding of the concepts and tools for building intelligent systems and applications. You’ll learn a range of new and different techniques, starting with simple linear progressing and regression to deep neural networks. With exercises and examples in each chapter to help you apply what you’ve learned, all you need is programming experience in any language to get started.
 
What you will learn
 
•             Use scikit-learn to track an example of end-to-end project in machine-learning
•             Explore several training models, including random forests, support vector machines, ensemble methods and decision trees
•             Explore different machine learning landscape, particularly neural nets
•             build and train neural nets from TensorFlow library
•             Dive into, convolution nets including neural net architectures, recurrent nets, and deep            reinforcement learning
•             Learn techniques for scaling and training deep neural nets
•             Apply practical code examples without acquiring excessive machine learning/Artificial               Intelligence theory or algorithm in details
 

• Learn the actual coding behind popular sites such as YouTube and Instagram that is in Python, a popular coding language used for most of the websites present nowadays.
• Learn TensorFlow, an open source library for numerical computation that makes machine learning easier and faster.
• Learn how to build models of linear regression.
• Make an image recognition model with CIFAR.
• Make a Credit or debit Card Fraud Detection Model using python language. Learn how to keep your data safe.

In this course, you will learn basics to high level Python language, its application and calculation of linear regression with TensorFlow, and use Artificial Intelligence and machine learning for automation in different industry.

Together with a professional in Python coding language with more than 10+ years of work and teaching experience you will easily perform CIFAR 10 image data recognition .At the end of this course it will be able to analyze credit and debit card fraud by building projects and models on it.

​This course comes up with study material for beginners to get comfortable and hands on with the interfaces of Python software. You can also find the following related courses in study material:

• Hands-On Image Recognition: Python Data Science Bootcamp!
• Fraud Detection with Python, TensorFlow & Linear Regression!
• Detect Fraud and Predict the Stock Market with TensorFlow