COVID-19 Outbreak Prediction
Instructor:
Mr. Bharani Akella
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Skills you will learn
About this course
Data Science is a magical field. With the help of Data Science, we can increase a company's market share, find customer sentiments over even understand the spread of a disease. In this course, we will be working on a covid-19 dataset and understand the spread of the disease. We will start off by building graphs for number of confirmed cases, cured cases and deaths using Seaborn library. Then, we will also analyze the spread of the virus across individual states. Finally, we will be building random forest regressor on top of the data to predict the number of confirmed cases with respect to date. Here, we will see how to build this algorithm and understand what is the efficacy of this. This course will also help you to improve your Exploratory Data Analysis skills as we will be extracting and working with a lot of individual records and variables from the given dataset.
Course Outline
This module begins by defining machine learning. It then discusses how a machine understands the tasks with examples and explains supervised and unsupervised learning concepts in machine learning.
This module focuses on sentiment analysis by helping you understand the sentiment associated with data. You will go through a hands-on example of implementing a logistic regression algorithm to analyze sentiment analysis using Python.
Unsupervised learning is a known machine learning method in which algorithms are not given pre-assigned labels to train the data. It self-discovers naturally occurring patterns in training the data sets.
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Our course instructor
Mr. Bharani Akella
Data Scientist
Data Science Expert
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