Generative Adversarial Networks (GAN) is one of the key domains of research in Advanced Machine Learning and Deep Learning Applications. It is used for text generation, forensic applications, network domain and many others
Tuesday, October 6, 2020
Saturday, June 20, 2020
Many times, there is need to concatenate and analyze multiple data frames in Python.
Suppose we have Three different Excel Sheets in which same type of attributes are there. From these excel sheets, the data can be imported to data frames and then analysis can be done.
Following are three different MS Excel Sheets of attendance of the candidates. From these sheets, we have to check whether a candidate attended all sessions or not
import pandas as pd
df1 = pd.read_excel (r'Book1.xlsx')
df1 = pd.DataFrame(df1, columns= ['Name', 'Attended'])
df2 = pd.read_excel (r'Book2.xlsx')
df2 = pd.DataFrame(df2, columns= ['Attended'])
df3 = pd.read_excel (r'Book3.xlsx')
df3 = pd.DataFrame(df3, columns= ['Attended'])
frames = [df1, df2, df3]
result = pd.concat(frames, axis=1, sort=False)
Sunday, April 19, 2020
Both containers and Virtual Machines address a similar issue — disconnection and control of parts of an application — however this is accomplished in various path as containers surrender a portion of the separation for a more effective use of the (host) framework assets.
$ docker ps
444413d7235233 b.gcr.io/tensorflow/tensorflow "/bin/bash" 2 minutes ago Up 2 minutes 6006/tcp, 0.0.0.0:8888->8888/tcp MyPath
$ docker-machine ls
default * virtualbox Running tcp://192.168.99.100:2376
<My IP Address>
192.168.99.100:8888(or whatever webserver port your web app is running on) and you should be able to see your web apps.
docker pull b.gcr.io/tensorflow/tensorflow-full
$ docker images
$ docker commit MyPath mypath/tensorflow
$ docker run mypath/tensorflow
Now, the container is ready for research purposes and implementation of algorithms.