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DS200A Computer Vision Assignment

Part Four: Neural networks

Build a neural network classifier using an architecture of your choosing. This application
of deep learning can be done in PyTorch, TensorFlow, or a framework of your choice. This is the
industry standard for image classification. Describe your network and assess its performance. To
receive extra credit, your neural network classifier must outperform your other methods.

!pip install tensorflow==2.0.0-alpha0
Requirement already satisfied: tensorflow==2.0.0-alpha0 in c:\programdata\anaconda3\envs\tensorflow_env\lib\site-packages (2.0.0a0) Requirement already satisfied: tb-nightly<1.14.0a20190302,>=1.14.0a20190301 in c:\programdata\anaconda3\envs\tensorflow_env\lib\site-packages (from tensorflow==2.0.0-alpha0) (1.14.0a20190301) Requirement already satisfied: wheel>=0.26 in c:\programdata\anaconda3\envs\tensorflow_env\lib\site-packages (from tensorflow==2.0.0-alpha0) (0.33.1) Requirement already satisfied: gast>=0.2.0 in c:\programdata\anaconda3\envs\tensorflow_env\lib\site-packages (from tensorflow==2.0.0-alpha0) (0.2.2) Requirement already satisfied: keras-preprocessing>=1.0.5 in c:\programdata\anaconda3\envs\tensorflow_env\lib\site-packages (from tensorflow==2.0.0-alpha0) (1.0.9) Requirement already satisfied: absl-py>=0.7.0 in c:\programdata\anaconda3\envs\tensorflow_env\lib\site-packages (from tensorflow==2.0.0-alpha0) (0.7.0) Requirement already satisfied: six>=1.10.0 in c:\programdata\anaconda3\envs\tensorflow_env\lib\site-packages (from tensorflow==2.0.0-alpha0) (1.12.0) Requirement already satisfied: tf-estimator-nightly<1.14.0.dev2019030116,>=1.14.0.dev2019030115 in c:\programdata\anaconda3\envs\tensorflow_env\lib\site-packages (from tensorflow==2.0.0-alpha0) (1.14.0.dev2019030115) Requirement already satisfied: google-pasta>=0.1.2 in c:\programdata\anaconda3\envs\tensorflow_env\lib\site-packages (from tensorflow==2.0.0-alpha0) (0.1.5) Requirement already satisfied: grpcio>=1.8.6 in c:\programdata\anaconda3\envs\tensorflow_env\lib\site-packages (from tensorflow==2.0.0-alpha0) (1.16.1) Requirement already satisfied: numpy<2.0,>=1.14.5 in c:\programdata\anaconda3\envs\tensorflow_env\lib\site-packages (from tensorflow==2.0.0-alpha0) (1.16.2) Requirement already satisfied: keras-applications>=1.0.6 in c:\programdata\anaconda3\envs\tensorflow_env\lib\site-packages (from tensorflow==2.0.0-alpha0) (1.0.7) Requirement already satisfied: astor>=0.6.0 in c:\programdata\anaconda3\envs\tensorflow_env\lib\site-packages (from tensorflow==2.0.0-alpha0) (0.7.1) Requirement already satisfied: protobuf>=3.6.1 in c:\programdata\anaconda3\envs\tensorflow_env\lib\site-packages (from tensorflow==2.0.0-alpha0) (3.6.1) Requirement already satisfied: termcolor>=1.1.0 in c:\programdata\anaconda3\envs\tensorflow_env\lib\site-packages (from tensorflow==2.0.0-alpha0) (1.1.0) Requirement already satisfied: werkzeug>=0.11.15 in c:\programdata\anaconda3\envs\tensorflow_env\lib\site-packages (from tb-nightly<1.14.0a20190302,>=1.14.0a20190301->tensorflow==2.0.0-alpha0) (0.15.2) Requirement already satisfied: markdown>=2.6.8 in c:\programdata\anaconda3\envs\tensorflow_env\lib\site-packages (from tb-nightly<1.14.0a20190302,>=1.14.0a20190301->tensorflow==2.0.0-alpha0) (3.0.1) Requirement already satisfied: h5py in c:\programdata\anaconda3\envs\tensorflow_env\lib\site-packages (from keras-applications>=1.0.6->tensorflow==2.0.0-alpha0) (2.9.0) Requirement already satisfied: setuptools in c:\programdata\anaconda3\envs\tensorflow_env\lib\site-packages (from protobuf>=3.6.1->tensorflow==2.0.0-alpha0) (41.0.0)
import tensorflow as tf
from sklearn.model_selection import train_test_split 
from sklearn.preprocessing import StandardScaler
import matplotlib.pyplot as plt
import numpy as np

print(tf.__version__)
2.0.0-alpha0