1. Study of Deep learning Packages: Tensorflow, Keras, Theano and PyTorch. Document the distinct features and functionality of the packages.

 1. Study of Deep learning Packages: Tensorflow, Keras, Theano and PyTorch. Document the distinct features and functionality of the packages.


Download The Write-up Here


Comments

Post a Comment

Popular posts from this blog

2. Implementing Feedforward neural networks with Keras and TensorFlow

  Download The Write-Up Here. # # Title of Assignment-2: # Implementing Feedforward neural networks with Keras and TensorFlow # a. Import the necessary packages # b. Load the training and testing data (MNIST) # c. Define the network architecture using Keras # d. Train the model using SGD # e. Evaluate the network # f. Plot the training loss and accuracy # # # Importing libraries # In[1]: #importing necessary libraries import tensorflow as tf from tensorflow import keras # In[2]: import pandas as pd import numpy as np import matplotlib . pyplot as plt import random get_ipython (). run_line_magic ( 'matplotlib' , 'inline' ) # # Loading and preparing the data # MNIST stands for “Modified National Institute of Standards and Technology”. # It is a dataset of 70,000 handwritten images. Each image is of 28x28 pixels # i.e. about 784 features. Each feature represents only one pixel’s intensity i.e. from 0(white) to 255(blac...
Read more