Introduction to Google Colab

Deep Learning focuses on the importance of ______ which differentiates it from traditional methods.

In image classification, a traditional approach may involve using ______ to determine if the game can be played.

Convolutional neural networks are often used for ______ tasks due to their capability to process pixel data effectively.

Every grayscale image can be represented as a ______ pixel image.

In a dataset, each pixel value from an image is treated as an ______ variable.

For colored images, the total number of pixels is ______ in a 20x20 image due to color channels.

Deep Learning removes the need for artificial fitting of ______ to classification data format.

The classification problem format must be defined in terms of ______ of the image data being processed.

Scatter plots are similar to line graphs as they use horizontal and vertical ______ to plot data points.

To focus on specific attributes in a scatter plot, you can specify the ______ you want to include.

Data cleaning involves handling missing features using methods such as dropna(), drop(), and [blank()].

One way to handle missing features is to set the values to some value like zero, the mean, or the ______.

Feature scaling ensures that attributes are on the same ______.

The two common methods to achieve the same scale in features are min-max scaling and ______.

Min-max scaling shifts and rescales values to range from ______ to 1.

Scikit-Learn provides a transformer called MinMaxScaler, which has a feature_range ______ to change the range.

The total number of records in the California Housing Prices dataset is ______.

A higher value of ______ indicates a house is farther west.

The ______ is a measure of how far north a house is.

The ______ variable includes the median house value measured in US Dollars.

The median income is measured in tens of thousands of US ______.

The total number of ______ within a block contributes to understanding the housing market.

The California Housing Prices dataset includes the feature ______ which describes the location of the house with respect to the ocean.

The ______ dataset consists of 70,000 small images of handwritten digits.

It is a library consisting of multidimensional array objects known as ______.

The library used for working with data sets, analyzing, and cleaning data is called ______.

Seaborn is a Python library for making ______ graphics.

Scikit-learn is a robust library used for ______ learning in Python.

The model used for grouping unlabeled data is called ______.

The command 'import pandas as ______' is used to include the Pandas library in Python.

The Python library built on top of Matplotlib for statistical graphics is called ______.

In Scikit-learn, the algorithms designed to predict outcomes based on labeled data are known as ______ learning algorithms.

Learn to manipulate and analyze data using ______.

Perform numerical computations with ______.

Create visualizations with ______ and Seaborn.

Understand machine learning concepts and apply them using ______.

Comprehend the concepts of descriptive statistics and ______ statistics.

Learn data transformation techniques essential for preparing datasets for ______.

Conduct exploratory data ______ to uncover insights.

Data Science is described as a field revolving around 5 data-related ______.