Using Tensorboard callback from Keras

If you are working with Keras library and want to use tensorboard to print your graphs of accuracy and other variables, Then below are the steps to follow. step 1: Initialize the keras callback library to import tensorboard by using below command from keras.callbacks import TensorBoard step 2: Include the below command in your program … Continue reading Using Tensorboard callback from Keras

30 things you can do with Pandas

Hello everyone!  Today I want to write about the Pandas library and here are the 30 things you can do with Pandas to better understand the data! First thing first, lets import pandas library: import pandas as pd df=pd.read_csv('test.csv') # read a test file to dataframe (1) Read in a CSV dataset pd.DataFrame.from_csv(“csv_file”) or pd.read_csv(“csv_file”) … Continue reading 30 things you can do with Pandas

My first Introduction with GAN ( Generative Adversarial Networks )

"it’s the coolest idea of Machine Learning in the last 20 years" - Yann LeCun (one of the fathers of Deep Learning) GANs or Generative Adversarial Networks are a kind of neural networks that is composed of 2 separate deep neural networks competing each other: the generator and the discriminator. Their goal is to generate … Continue reading My first Introduction with GAN ( Generative Adversarial Networks )