Python 2022实现完整的卷积神经网络

深度学习卷积神经网络(CNN) – Keras & TensorFlow 2

你会学到什么
深梦
数据扩充
利用光彩造型修护发膏
开始
数据扩充
Con2D
MaxPooling2D
提前停止
Matplotlib
混淆矩阵
熊猫
数组
最小最大缩放器
Google Colab
深度学习。
训练神经网络。
将数据分为训练集和测试集。
测试准确性。
混乱矩阵。
做个预测。
模型编译。

MP4 |视频:h264，1280×720 |音频:AAC，44.1 KHz，2声道
语言：英语+中英文字幕（云桥CG资源站 机译） |时长:31节课(5小时57分钟)|大小解压后:2.56 GB 含课程文件


要求
需要基本的Python和机器学习知识

描述
对机器学习、深度学习、人工智能领域感兴趣？那么这道菜就是为你准备的！

这门课程是由一位软件工程师设计的。我希望凭借我多年来获得的经验和知识，我可以分享我的知识，并帮助您以简单的方式学习复杂的理论、算法和代码库。

我会一步一步带你进入深度学习。通过每一个教程，你将发展新的技能，并提高你对这个充满挑战但利润丰厚的数据科学子领域的理解。The Complete Convolutional Neural Network with Python 2022

这门课程有趣又令人兴奋，但同时，我们也深入研究了递归神经网络。在课程的全新版本中，我们涵盖了大量的工具和技术，包括

深度学习。

Google Colab

喀拉斯。

Matplotlib。

将数据分为训练集和测试集。

训练神经网络。

模型构建。

分析结果。

模型编译。

做个预测。

测试准确性。

混乱矩阵。

自动编码器。

Numpy。

熊猫。

张量流。

情感分析。

Matplotlib。

深梦

开始

数据扩充

Conv2D

MaxPooling2D

提前停止

利用光彩造型修护发膏

最大缩放器。

此外，本课程还包含了基于真实例子的实践练习。因此，你不仅会学到理论，还会得到一些构建自己模型的实践机会。有几个项目供你练习和积累知识。这些项目列举如下

CIFAR-10。

图像组合。

影评感悟。

服装形象。

这门课程是给谁的
任何对深度学习、机器学习和人工智能感兴趣的人
至少具备高中数学知识，并且希望开始学习机器学习、深度学习和人工智能的学生
任何想要在机器学习、深度学习和人工智能方面提升水平的数据分析师。
任何对人工智能充满热情的人
希望将其人工智能技能提升到更高水平的数据科学家

MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 31 lectures (5h 57m) | Size: 2.48 GB

Deep Learning Convolutional Neural Network (CNN) – Keras & TensorFlow 2

What you’ll learn
DeepDream
Data augmentation
VGG
Inception
Data augmentation
Con2D
MaxPooling2D
EarlyStopping
Matplotlib
Confusion matrix
Pandas
Numpy
MinMaxScaler
Google Colab
Deep Learning.
Training Neural Network.
Splitting Data into Training Set and Test Set.
Testing Accuracy.
Confusion Matrix.
Make a Prediction.
Model compilation.

Requirements
Basic Python and machine learning knowledge is required

Description
Interested in the field of Machine Learning, Deep Learning, and Artificial Intelligence? Then this course is for you!

This course has been designed by a software engineer. I hope with the experience and knowledge I did gain throughout the years, I can share my knowledge and help you learn complex theories, algorithms, and coding libraries in a simple way.

I will walk you step-by-step into Deep Learning. With every tutorial, you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science.

This course is fun and exciting, but at the same time, we dive deep into Recurrent Neural Network. Throughout the brand new version of the course, we cover tons of tools and technologies including

Deep Learning.

Google Colab

Keras.

Matplotlib.

Splitting Data into Training Set and Test Set.

Training Neural Network.

Model building.

Analyzing Results.

Model compilation.

Make a Prediction.

Testing Accuracy.

Confusion Matrix.

Autoencoder.

Numpy.

Pandas.

Tensorflow.

Sentiment Analysis.

Matplotlib.

DeepDream

Inception

Data Augmentation

Conv2D

MaxPooling2D

Early Stopping

VGG

MinMaxScaler.

Moreover, the course is packed with practical exercises that are based on real-life examples. So not only will you learn the theory, but you will also get some hands-on practice building your own models. There are several projects for you to practice and build up your knowledge. These projects are listed below

CIFAR-10.

Image Combination.

Movie Review sentiment.

Clothing Image.

Who this course is for
Anyone interested in Deep Learning, Machine Learning and Artificial Intelligence
Students who have at least high school knowledge in math and who want to start learning Machine Learning, Deep Learning, and Artificial Intelligence
Any data analysts who want to level up in Machine Learning, Deep Learning and Artificial Intelligence.
Anyone passionate about Artificial Intelligence
Data Scientists who want to take their AI Skills to the next level

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