文件名称:neural-networks-and-deep-learning:这是我在吴安德(Andrew Ng)课程“神经网络与深度学习”中的作业
文件大小:26.81MB
文件格式:ZIP
更新时间:2024-05-23 14:55:24
JupyterNotebook
神经网络与深度学习 这是我对吴安德(Andrew Ng)的特殊课程“”的分配,该特殊课程包括五门课程: 在本课程中,您将学习深度学习的基础。 完成本课程后,您将: 了解推动深度学习的主要技术趋势 能够构建,训练和应用完全连接的深度神经网络 知道如何实现有效的(矢量化)神经网络 了解神经网络架构中的关键参数 本课程还教您深度学习的实际工作原理,而不是仅提供粗略的描述或表面描述。 因此,完成学习后,您将能够将深度学习应用于自己的应用程序。 如果您正在寻找AI的工作,在完成此课程后,您还可以回答基本的面试问题。 编程作业: 带有Numpy的Python基础知识 神经网络心态v3的Logistic回归 具有一个隐藏层v3的平面数据分类 逐步构建您的深度神经网络v3 深度神经网络应用程序v3 [笔记本] [py] 改善深度神经网络:超参数调整,正则化和优化 完成本课程后,您将:
【文件预览】:
neural-networks-and-deep-learning-master
----notebook()
--------Logistic Regression with a Neural Network mindset v3.ipynb(763KB)
--------Residual Networks .ipynb(339KB)
--------Optimization methods.ipynb(361KB)
--------Deep Neural Network Application v3.ipynb(1.95MB)
--------Regularization.ipynb(272KB)
--------Keras Tutorial Happy House v2.ipynb(59KB)
--------Building a Recurrent Neural Network Step by Step v3.ipynb(88KB)
--------Convolution model Step by Stepv1.ipynb(60KB)
--------Gradient Checking.ipynb(26KB)
--------Neural machine translation with attention.ipynb(85KB)
--------Art Generation with Neural Style Transfer.ipynb(44KB)
--------Planar data classification with one hidden layer v3.ipynb(385KB)
--------Operations on word vectors.ipynb(33KB)
--------Dinosaurus Island Character level language model final v3.ipynb(45KB)
--------Emojify.ipynb(68KB)
--------Trigger word detection.ipynb(14MB)
--------Face Recognition for the Happy House.ipynb(40KB)
--------Initialization.ipynb(268KB)
--------Python Basics With Numpy v3.ipynb(41KB)
--------Tensorflow Tutorial.ipynb(204KB)
--------Building your Deep Neural Network Step by Step v3.ipynb(55KB)
--------Autonomous driving application Car detection.ipynb(213KB)
--------Convolution model Application v1.ipynb(66KB)
----py()
--------Dinosaurus Island Character level language model final v3.py(29KB)
--------Building your Deep Neural Network Step by Step v3.py(38KB)
--------Building a Recurrent Neural Network Step by Step v3.py(60KB)
--------Initialization.py(17KB)
--------Operations on word vectors.py(22KB)
--------Residual Networks .py.html(29KB)
--------Logistic Regression with a Neural Network mindset v3.py(29KB)
--------Face Recognition for the Happy House.py.html(23KB)
--------Optimization methods.py(42KB)
--------Regularization.py(28KB)
--------Tensorflow Tutorial.py(37KB)
--------Python Basics With Numpy v3.py(23KB)
--------Planar data classification with one hidden layer v3.py(29KB)
--------Art Generation with Neural Style Transfer.py.html(32KB)
--------Convolution model Application v1.py.html(21KB)
--------Autonomous driving application Car detection.py.html(36KB)
--------Convolution model Step by Step v1.py.html(37KB)
--------Neural machine translation with attention.py(24KB)
--------Keras Tutorial Happy House v2.py.html(14KB)
--------Gradient Checking.py(19KB)
--------Deep Neural Network Application v3.py(20KB)
--------Emojify.py(33KB)
--------Trigger word detection.py(40KB)
----README.md(13KB)
----course-note.pdf(19.13MB)