Neural Network Projects with Python
暫譯: 使用 Python 的神經網絡專案

Loy, James

Neural Network Projects with Python

商品描述

Key Features

  • Discover neural network architectures (like CNN and LSTM) that are driving recent advancements in AI
  • Build expert neural networks in Python using popular libraries such as Keras
  • Includes projects such as object detection, face identification, sentiment analysis, and more

Book Description

Neural networks are at the core of recent AI advances, providing some of the best resolutions to many real-world problems, including image recognition, medical diagnosis, text analysis, and more. This book goes through some basic neural network and deep learning concepts, as well as some popular libraries in Python for implementing them.

It contains practical demonstrations of neural networks in domains such as fare prediction, image classification, sentiment analysis, and more. In each case, the book provides a problem statement, the specific neural network architecture required to tackle that problem, the reasoning behind the algorithm used, and the associated Python code to implement the solution from scratch. In the process, you will gain hands-on experience with using popular Python libraries such as Keras to build and train your own neural networks from scratch.

By the end of this book, you will have mastered the different neural network architectures and created cutting-edge AI projects in Python that will immediately strengthen your machine learning portfolio.

What you will learn

  • Learn various neural network architectures and its advancements in AI
  • Master deep learning in Python by building and training neural network
  • Master neural networks for regression and classification
  • Discover convolutional neural networks for image recognition
  • Learn sentiment analysis on textual data using Long Short-Term Memory
  • Build and train a highly accurate facial recognition security system

Who this book is for

This book is a perfect match for data scientists, machine learning engineers, and deep learning enthusiasts who wish to create practical neural network projects in Python. Readers should already have some basic knowledge of machine learning and neural networks.

商品描述(中文翻譯)

**主要特點**

- 探索推動近期人工智慧進展的神經網絡架構（如 CNN 和 LSTM）
- 使用流行的 Python 函式庫（如 Keras）構建專業的神經網絡
- 包含物件檢測、人臉識別、情感分析等專案

**書籍描述**

神經網絡是近期人工智慧進展的核心，為許多現實世界問題提供了最佳解決方案，包括圖像識別、醫療診斷、文本分析等。本書介紹了一些基本的神經網絡和深度學習概念，以及在 Python 中實現這些概念的一些流行函式庫。

本書包含在票價預測、圖像分類、情感分析等領域的神經網絡實際示範。在每個案例中，書中提供了問題陳述、解決該問題所需的特定神經網絡架構、所用算法的推理，以及從頭開始實現解決方案的相關 Python 代碼。在此過程中，您將獲得使用流行的 Python 函式庫（如 Keras）構建和訓練自己的神經網絡的實踐經驗。

在本書結束時，您將掌握不同的神經網絡架構，並在 Python 中創建尖端的人工智慧專案，這將立即增強您的機器學習作品集。

**您將學到的內容**

- 學習各種神經網絡架構及其在人工智慧中的進展
- 通過構建和訓練神經網絡掌握 Python 中的深度學習
- 精通用於回歸和分類的神經網絡
- 探索用於圖像識別的卷積神經網絡
- 使用長短期記憶（Long Short-Term Memory）學習文本數據的情感分析
- 構建和訓練一個高準確度的人臉識別安全系統

**本書適合誰**

本書非常適合希望在 Python 中創建實用神經網絡專案的數據科學家、機器學習工程師和深度學習愛好者。讀者應該已經具備一些基本的機器學習和神經網絡知識。

目錄大綱

  1. Machine Learning and Neural Networks 101
  2. Predicting Diabetes with Multilayer Perceptrons
  3. Predicting Taxi Fares with Deep Feedforward Networks
  4. Cats Versus Dogs - Image Classification Using CNNs
  5. Removing Noise from Images Using Autoencoders
  6. Sentiment Analysis of Movie Reviews Using LSTM
  7. Implementing a Facial Recognition System with Neural Networks
  8. What’s Next?

目錄大綱(中文翻譯)


  1. Machine Learning and Neural Networks 101

  2. Predicting Diabetes with Multilayer Perceptrons

  3. Predicting Taxi Fares with Deep Feedforward Networks

  4. Cats Versus Dogs - Image Classification Using CNNs

  5. Removing Noise from Images Using Autoencoders

  6. Sentiment Analysis of Movie Reviews Using LSTM

  7. Implementing a Facial Recognition System with Neural Networks

  8. What’s Next?

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