کتابخانه مهندسی کامپیوتر و پایتون
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Deep Learning with Applications Using Python

Author: Navin Kumar Manaswi


Description:
Explore deep learning applications, such as computer vision, speech recognition, and chatbots, using frameworks such as TensorFlow and Keras. This book helps you to ramp up your practical know-how in a short period of time and focuses you on the domain, models, and algorithms required for deep learning applications. Deep Learning with Applications Using Python covers topics such as chatbots, natural language processing, and face and object recognition. The goal is to equip you with the concepts, techniques, and algorithm implementations needed to create programs capable of performing deep learning.
This book covers convolutional neural networks, recurrent neural networks, and multilayer perceptrons. It also discusses popular APIs such as IBM Watson, Microsoft Azure, and scikit-learn.
#پایتون #یادگیری_عمیق

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Deep_Learning_with_Applications_Using_Python_Chatbots_and_Face,.pdf
11.3 MB
📘Deep Learning with Applications Using Python - 2018

▪️What You Will Learn

Work with various deep learning frameworks such as TensorFlow, Keras, and scikit-learn.

Use face recognition and face detection capabilities

Create speech-to-text and text-to-speech functionality

Engage with chatbots using deep learning


︎ Who This Book Is For
Data scientists and developers who want to adapt and build deep learning applications.

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📘Building Django 2.0 Web Applications: Create enterprise-grade, scalable Python web applications easily with Django 2.0

✒️Tom Aratyn (2018)

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Building_Django_2_0_Web_Applications_Create_enterprise_grade,_scalable.pdf
2.3 MB
Building Django 2.0 Web Applications: Create enterprise-grade, scalable Python web applications easily with Django 2.0
Tom Aratyn (2018)

@Programming4all_0to100
RHCSA Red Hat Enterprise Linux 8: Training and Exam Preparation Guide (EX200)


Author(s): Asghar Ghori
Publisher: Asghar Ghori, Year: 2020

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Linux @Max_Academy.pdf
69.1 MB
Description:
This book has 21 chapters that are organized logically. It covers the topics on local RHEL 8 installation; initial interaction with the system and basic commands; compression and archiving; file editing and manipulation; standard and special permissions; file searching and access controls; user monitoring and authentication files; users, groups, and password aging; bash shell features and startup files; processes and task scheduling; basic and advanced software administration techniques; system boot process and bootloader; kernel management and system initialization; logging and system tuning; basic and advanced storage management tools and solutions; local and remote file systems and swap regions; network device and connection configuration; time synchronization and hostname resolution; the secure shell service; and firewall and SELinux controls.

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Ng-Book: The Complete Guide to Angular 9



Author(s): Nathan Murray; Felipe Coury; Ari Lerner; Carlos Taborda
Publisher: Fullstack.io, Year: 2020


Description:
The in-depth, complete, and up-to-date book on Angular 9. Become an Angular 9 expert today

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📘Raspberry Pi Computer Vision Programming: Design and implement computer vision applications with Raspberry Pi, OpenCV, and Python 3, 2nd Edition. Code

▪️Author(s): Ashwin Pajankar
Publisher: Packt Publishing, Year: 2020

▪️Description:
Code .
Perform a wide variety of computer vision tasks such as image processing and manipulation, feature and object detection, and image restoration to build real-life computer vision applications

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#پایتون #اینترنت_اشیا #آردوینو #رزبری‌پای

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Raspberry pi @Max_Academy.pdf
12.2 MB
▪️What you will learn

Set up a Raspberry Pi for computer vision applications

Perform basic image processing with libraries such as NumPy, Matplotlib, and OpenCV

Demonstrate arithmetical, logical, and other operations on images

Work with a USB webcam and the Raspberry Pi Camera Module

Implement low-pass and high-pass filters and understand their applications in image processing

Cover advanced techniques such as histogram equalization and morphological transformations

Create GUI apps with Python 3 and OpenCV

Perform machine learning with K-means clustering and image quantization

▪️Who this book is for

This book is for beginners as well as experienced Raspberry Pi and Python 3 enthusiasts who are looking to explore the amazing world of computer vision. Working knowledge of the Python 3 programming language

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#پایتون #اینترنت_اشیا #آردوینو #رزبری‌پای
#OpenCV
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Pro Machine Learning Algorithms

Author(s): V Kishore Ayyadevara
Publisher: Apress, Year: 2018


Description:
Bridge the gap between a high-level understanding of how an algorithm works and knowing the nuts and bolts to tune your models better. This book will give you the confidence and skills when developing all the major machine learning models. In Pro Machine Learning Algorithms, you will first develop the algorithm in Excel so that you get a practical understanding of all the levers that can be tuned in a model, before implementing the models in Python/R.
You will cover all the major algorithms: supervised and unsupervised learning, which include linear/logistic regression; k-means clustering; PCA; recommender system; decision tree; random forest; GBM; and neural networks. You will also be exposed to the latest in deep learning through CNNs, RNNs, and word2vec for text mining.
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#پایتون #یادگیری_ماشین

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Pro Machine Learning Algorithms.pdf
22.2 MB
Pro Machine Learning Algorithms - 2018

What You Will Learn

Get an in-depth understanding of all the major machine learning and deep learning algorithms

Fully appreciate the pitfalls to avoid while building models

Implement machine learning algorithms in the cloud

Follow a hands-on approach through case studies for each algorithm

Gain the tricks of ensemble learning to build more accurate models

Discover the basics of programming in R/Python and the Keras framework for deep learning

Who This Book Is For
Business analysts/ IT professionals who want to transition into data science roles. Data scientists who want to solidify their knowledge in machine learning.

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Coding the Arduino: Building Fun Programs, Games, and Electronic Projects

Author(s): Bod Dukish
Series: Technology in Action
Publisher: Apress, Year: 2018

Description:

Get started with Arduino and computer coding. This book is intended for those new to the Arduino and computer coding. and looking to gain the skills to write microcontroller programs that can act on given inputs and operate electromechanical output devices. 
Coding the Arduino contains four sections: background information, game development, electronic games and projects, and expanded programs. The final chapters expand on the functionality of some of the programs presented in previous chapters, and challenges you with capstone projects. 
The projects will be described where the program code that is presented can be modified, or in which two or more of the sample programs may be used to  be used to synthesize a new program as the solution to the problem that is presented

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Coding the Arduino.pdf
32.8 MB
📘Coding the Arduino: Building Fun Programs, Games, and Electronic Projects

▪️What You'll Learn:

Understand basic principles of technology, and about analog and digital electronics.

Create games from scratch, where you interactively play against the program.

Gain an introduction to Artificial Intelligence (AI)

▪️Who This Book Is For:
Electronic hobbyists and makers of all levels looking to get started with Arduinos. 

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#پایتون #اینترنت_اشیا #آردوینو #رزبری‌پای

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Machine Learning with the Raspberry Pi: Experiments with Data and Computer Visio

Author(s): Donald J. Norris
Series: Technology in Action
Publisher: Apress, Year: 2019

Description:
Using the Pi Camera and a Raspberry Pi board, expand and replicate interesting machine learning (ML) experiments.
This book provides a solid overview of ML and a myriad of underlying topics to further explore. Non-technical discussions temper complex technical explanations to make the hottest and most complex topic in the hobbyist world of computing understandable and approachable.

Machine learning, also commonly referred to as deep learning (DL), is currently being integrated into a multitude of commercial products as well as widely being used in industrial, medical, and military applications. It is hard to find any modern human activity, which has not been "touched" by artificial intelligence (AI) applications.

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