Deep Learning - Deep Neural Network for Beginners Using Python - Coding Perceptron Algo (Data Reading and Visualization)

The video tutorial introduces the use of Pandas, Numpy, and Matplotlib libraries for data analysis. It demonstrates how to read data from an Excel file into a Pandas dataframe, partition the data into features and labels, and visualize it using scatter plots. The tutorial also covers converting data into Numpy arrays and provides a brief overview of the perceptron step to be covered in the next lecture.

Which library is used for reading data in the tutorial?

• Matplotlib

• Numpy

• Scikit-learn

• Pandas

What is the purpose of setting 'header' to 'none' when reading the data?

• To read only the header

• To exclude the header from the data

• To format the header

• To include the header in the data

How many columns are used as features in the data partitioning step?

• Two

• One

• Three

• Four

What does the 'X' variable represent in the data partitioning process?

• Features

• Labels

• Indices

• Headers

Which function is used to create a scatter plot in the tutorial?

• plt.bar

• plt.hist

• plt.scatter

• plt.line

What color is used to represent the label '1' in the scatter plot?

• Yellow

• Red

• Green

• Blue

What is the next topic to be covered after data visualization?

• Data cleaning

• Perceptron step

• Regression analysis

• Clustering