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Искусственный Интеллект с Python Книга

ChernenkoSergey/Artificial-Intelligence-with-Python-Book

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NumPy SciPy scikit-learn Matplotlib Tkinter NLTK(Natural Language Toolkit) Gensim Pattern pandas hmmlearn PyStruct CVXOPT numpy+mkl python_speech_features kanren SymPy DEAP(Distributed Evolutionary Algorithms in Python) easyAI OpenCV NeuroLab OpenAI Gym TensorFlow

Глава 1 «Введение в искусственный интеллект» Не содержит код

Книга «Искусственный Интеллект с Python» Автор Prateek Joshi

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Искусственный Интеллект с Python Книга

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Code repository for Artificial Intelligence with Python, published by Packt

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PacktPublishing/Artificial-Intelligence-with-Python

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Artificial Intelligence with Python

This is the code repository for Artificial Intelligence with Python, published by Packt. It contains all the supporting project files necessary to work through the book from start to finish.

During the course of this book, you will find out how to make informed decisions about what algorithms to use in a given context. Starting from the basics of Artificial Intelligence, you will learn how to develop various building blocks using different data mining techniques. You will see how to implement different algorithms to get the best possible results, and will understand how to apply them to real-world scenarios. If you want to add an intelligence layer to any application that’s based on images, text, stock market, or some other form of data, this exciting book on Artificial Intelligence will definitely be your guide!

##Instructions and Navigation All of the code is organized into folders. Each folder starts with a number followed by the application name. For example, Chapter02.

The code will look like the following:

A block of code is set as follows: [default] exten => s,1,Dial(Zap/1|30) exten => s,2,Voicemail(u100) exten => s,102,Voicemail(b100) exten => i,1,Voicemail(s0) 

This book is focused on artificial intelligence in Python as opposed to the Python itself. We have used Python 3 to build various applications. We focus on how to utilize various Python libraries in the best possible way to build real world applications. In that spirit, we have tried to keep all of the code as friendly and readable as possible. We feel that this will enable our readers to easily understand the code and readily use it in different scenarios.

Click here if you have any feedback or suggestions.

If you have already purchased a print or Kindle version of this book, you can get a DRM-free PDF version at no cost.
Simply click on the link to claim your free PDF.

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Code repository for Artificial Intelligence with Python, published by Packt

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Artificial Intelligence with Python – Sequence Learning, Packt Publishing

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PacktPublishing/Artificial-Intelligence-with-Python-Sequence-Learning

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Artificial Intelligence with Python — Sequence Learning [Video]

This is the code repository for Artificial Intelligence with Python — Sequence Learning [Video], published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.

Enter and explore the fascinating world of intelligent apps with Artificial Intelligence with Python. Artificial Intelligence is becoming increasingly relevant in the modern world. By harnessing the power of algorithms, you can create apps that intelligently interact with the world around you, automatic speech recognition systems, and more.

• Build automatic speech recognition systems
• Discover how to build intelligent applications centered on text and time series data

Instructions and Navigation

To fully benefit from the coverage included in this course, you will need:
Basic knowledge of python is necessary

This course has the following software requirements:
Python 3.x

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Artificial Intelligence with Python Cookbook, published by Packt

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Artificial Intelligence with Python Cookbook

This is the code repository for Artificial Intelligence with Python Cookbook, published by Packt.

Practical recipes for next-generation deep learning and neural networks using TensorFlow and PyTorch

With artificial intelligence (AI) systems, we can develop goal-driven agents to automate problem-solving. This involves predicting and classifying the available data and training agents to execute tasks successfully. This book will help you to solve complex AI problems using practical recipes.

This book covers the following exciting features:

• Implement data preprocessing steps and optimize model hyperparameters
• Work with large amounts of data using distributed and parallel computing techniques
• Get to grips with representational learning from images using InfoGAN
• Delve into deep probabilistic modeling with a Bayesian network
• Create your own artwork using adversarial neural networks

If you feel this book is for you, get your copy today!

Instructions and Navigations

All of the code is organized into folders. For example, Chapter02.

The code will look like the following:

from sklearn.datasets import fetch_openml data = fetch_openml(data_id=42165, as_frame=True) 

Following is what you need for this book: This AI book is for Python developers, data scientists, machine learning developers, and deep learning practitioners who want to learn how to build artificial intelligence solutions with easy-to-follow recipes. If you are looking for state-of-the-art solutions to perform different machine learning tasks in various use cases, this book is for you. Basic working knowledge of Python programming language and machine learning concepts will help you to work with the code.

With the following software and hardware list you can run all code files present in the book (Chapter 1-11).

Software and Hardware List

Chapter	Software required	OS required
1	Python 3.6 or later	Windows, Mac OS X, and Linux (Any)
2	TensorFlow 2.0 or later	Windows, Mac OS X, and Linux (Any)
3	PyTorch 1.6 or later	Windows, Mac OS X, and Linux (Any)
4	Pandas 1.0 or later	Windows, Mac OS X, and Linux (Any)
5	Scikit-learn 0.22.0 or later	Windows, Mac OS X, and Linux (Any)

We also provide a PDF file that has color images of the screenshots/diagrams used in this book. Click here to download it.

• Hands-On Artificial Intelligence for Banking [Packt][Amazon]
• Artificial Intelligence with Python — Second Edition [Packt][Amazon]

Ben Auffarth is a full-stack data scientist with more than 15 years of work experience. With a background and Ph.D. in computational and cognitive neuroscience, he has designed and conducted wet lab experiments on cell cultures, analyzed experiments with terabytes of data, run brain models on IBM supercomputers with up to 64k cores, built production systems processing hundreds of thousands of transactions per day, and trained neural networks on millions of text documents. He resides in West London with his family, where you might find him in a playground with his young son. He co-founded and is the former president of Data Science Speakers, London.

Click here if you have any feedback or suggestions.

If you have already purchased a print or Kindle version of this book, you can get a DRM-free PDF version at no cost.
Simply click on the link to claim your free PDF.

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Artificial Intelligence with Python Cookbook, published by Packt

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