文件列表:

CODEOWNERS (42, 2021-10-21)
LICENSE (1064, 2021-10-21)
Matplotlib (0, 2021-10-21)
Matplotlib\Additional_Plot_Practice.ipynb (9694, 2021-10-21)
Matplotlib\Bar_Chart_Practice.ipynb (4479, 2021-10-21)
Matplotlib\Categorical_Plot_Practice.ipynb (2215, 2021-10-21)
Matplotlib\Histogram_Practice.ipynb (1883, 2021-10-21)
Matplotlib\Scales_and_Transformations_Practice.ipynb (2612, 2021-10-21)
Matplotlib\Scatterplot_Practice.ipynb (2963, 2021-10-21)
Matplotlib\Violin_and_Box_Plot_Practice.ipynb (2117, 2021-10-21)
Matplotlib\data (0, 2021-10-21)
Matplotlib\data\fuel_econ.csv (585225, 2021-10-21)
Matplotlib\data\pokemon.csv (45254, 2021-10-21)
Matplotlib\solutions_biv.py (8938, 2021-10-21)
Matplotlib\solutions_univ.py (4485, 2021-10-21)
NumPy Mini-Project (0, 2021-10-21)
NumPy Mini-Project\Mean Normalization and Data Separation.ipynb (8917, 2021-10-21)
NumPy Mini-Project\Solution.ipynb (11875, 2021-10-21)
Pandas Mini-Project (0, 2021-10-21)
Pandas Mini-Project\AAPL.csv (310688, 2021-10-21)
Pandas Mini-Project\AMZN.csv (319257, 2021-10-21)
Pandas Mini-Project\GOOG.csv (245196, 2021-10-21)
Pandas Mini-Project\Statistics from Stock Data - Solution.ipynb (53359, 2021-10-21)
Pandas Mini-Project\Statistics from Stock Data.ipynb (11494, 2021-10-21)
intropylab-classifying-images (0, 2021-10-21)
intropylab-classifying-images\alternative-to-classify_images.py (8804, 2021-10-21)
intropylab-classifying-images\check_images.py (11263, 2021-10-21)
intropylab-classifying-images\check_images_hints.py (32259, 2021-10-21)
intropylab-classifying-images\check_images_solution.py (23491, 2021-10-21)
intropylab-classifying-images\classifier.py (2561, 2021-10-21)
intropylab-classifying-images\command_line_arguments.py (1379, 2021-10-21)
intropylab-classifying-images\create_pet_image_labels.py (2853, 2021-10-21)
intropylab-classifying-images\data_structure.py (3232, 2021-10-21)
intropylab-classifying-images\dognames.txt (4066, 2021-10-21)
... ...

# AIPND This repository contains code and associated files for the AI Programming with Python Nanodegree program. This repository consists of a number of tutorial notebooks for various coding exercises and programming labs that will be used to supplement the lessons of the course. ## Table Of Contents ### Tutorial Notebooks * Linear Algebra Essentials * [Vectors Lab](https://github.com/udacity/AIPND/tree/master/linearalgebra-vectors_lab "Vectors Lab") Learn how to graph 2D vectors. * [Linear Combination Lab](https://github.com/udacity/AIPND/tree/master/linearalgebra-linear_combination "Linear Combination Lab") Learn how to computationally determine a vector's span and solve a simple system of equations. * [Linear Mapping](https://github.com/udacity/AIPND/tree/master/linearalgebra-linear_mapping "Linear Mapping Labs") Learn how to solve some problems computationally using vectors and matrices. ### Programming Labs * [Intro to Python Lab - Classifying Images Lab:](https://github.com/udacity/AIPND/tree/master/intropylab-classifying-images "Classifying Images Lab") Determine which CNN architecture model works best at classifying images of dogs and their breeds. ### NumPy and Pandas Mini-Projects * [NumPy Mini-Project](https://github.com/udacity/AIPND/tree/master/NumPy%20Mini-Project) Mean normalize and separate data * [Pandas Mini-Project](https://github.com/udacity/AIPND/tree/master/Pandas%20Mini-Project) Get statistics from stock data ### Matplotlib * [Matplotlib](https://github.com/udacity/AIPND/tree/master/Matplotlib) Notebooks containing practice exercises for the Matplotlib lesson(s) ### Quiz Notes * [Notes:](https://github.com/udacity/AIPND/tree/master/notes "Notes") This directory contains more information about certain quizzes that are testing more challenging concepts. The filename indicates which _quiz_ the note is covering. Additionally, one will find the [Frequently Asked Questions](https://github.com/udacity/AIPND/blob/master/notes/lab_intro-to-python-lab.md) for the _Intro to Python Lab_. Click on the filename to view the contents of the notes on a _quiz_ or the _Intro to Python Lab_. ## Dependencies Each directory has a `requirements.txt` describing the minimal dependencies required to run the notebooks in that directory. ### pip To install these dependencies with pip, you can issue `pip3 install -r requirements.txt`.

近期下载者：

相关文件：

评论：[我要评论] [举报此文件]

收藏者：