If the data shows a curvy trend, then linear regression will not produce very accurate results when compared to a non-linear regression because, as the name implies, linear regression presumes that the data is linear. Let’s learn about non-linear regressions and apply an example in python. …
The objective of this blog is to design a Deep Learning model i.e. an Artificial Neural Network Model to predict if customers of the bank will remain with a bank or if they will leave the bank and its services.
The dataset which we will be using is ChurnData.csv to…
Traffic Signs Recognition using Deep Learning i.e. Convolutional Neural Network (CNN)
One of the applications where deep learning is being used extensively is Autonomous Driving. The autonomous driving mechanism needs to detect innumerable objects (pedestrians, other cars, obstacles, etc.) and make decisions. One of the smaller problems is to detect…
“Word clouds (also known as text clouds or tag clouds) work in a simple way: the more a specific word appears in a source of textual data (such as a speech, blog post, or database), the bigger and bolder it appears in the word cloud.”
First of all, let’s import…
Welcome to this blog about Autoencoders. In this blog, you will find an explanation of what is an autoencoder, how it works, and see an implementation of an autoencoder in TensorFlow.
An autoencoder, also known as Autoassociator or Diabolo networks…
A Choropleth map is a thematic map in which areas are shaded or patterned in proportion to the measurement of the statistical variable being displayed on the map, such as population density or per-capita income. The choropleth map provides an easy way to visualize how a measurement varies across a…
Let’s download and import the data on police department incidents using pandas `read_csv()` method.
Download the dataset and read it into a pandas dataframe:
df_incidents = pd.read_csv('https://s3-api.us-geo.objectstorage.softlayer.net/cf-courses-data/CognitiveClass/DV0101EN/labs/Data_Files/Police_Department_Incidents_-_Previous_Year__2016_.csv')print('Dataset downloaded and read into a pandas dataframe!')
Let’s take a look at the first five items in our dataset.
df_incidents.head()
In this blog, you will learn how to create maps for different objectives. To do that, we will part ways with Matplotlib and work with another Python visualization library, namely Folium. What is nice about Folium is that it was developed for the sole purpose of visualizing geospatial data. While…
