Write a title that briefly explains what it is about. Between 20 and 90, Exercises of Computer Vision

Download Write a title that briefly explains what it is about. Between 20 and 90 and more Exercises Computer Vision in PDF only on Docsity! Instructions: In this Lab, you will demonstrate the data regression skills you have learned by completing this course. You are expected to leverage a wide variety of tools, but also this report should focus on present findings, insights, and next steps. You may include some visuals from your code output, but this report is intended as a summary of your findings, not as a code review. The grading will center around 5 main points: 1. Does the report include a section describing the data? 2. Does the report include a paragraph detailing the main objective(s) of this analysis? 3. Does the report include a section with variations of linear regression models and specifies which one is the model that best suits the main objective(s) of this analysis. 4. Does the report include a clear and well-presented section with key findings related to the main objective(s) of the analysis? 5. Does the report highlight possible flaws in the model and a plan of action to revisit this analysis with additional data or different predictive modeling techniques? Import the required libraries The following required modules are pre-installed in the Skills Network Labs environment. However if you run this notebook commands in a different Jupyter environment (e.g. Watson Studio or Ananconda) you will need to install these libraries by removing the # sign before !mamba in the code cell below. In [ ]: # All Libraries required for this lab are listed below. The libraries pre-installed on Skills Network Labs are commented. # !mamba install -qy pandas==1.3.4 numpy==1.21.4 seaborn==0.9.0 matplotlib==3.5.0 scikit-learn==0.20.1 # Note: If your environment doesn't support "!mamba install", use "!pip install" In [ ]: import pandas as pd Importing the Dataset Before you begin, you will need to choose a data set that you feel passionate about or you can use data set of insurance.csv file. Read your chosen dataset into pandas dataframe: In [ ]: #data = pd.read_csv('Data/ insurance.csv') #data.head() Once you have selected a data set, you will produce the deliverables listed below and submit them to one of your peers for review. Treat this exercise as an opportunity to produce analysis that are ready to highlight your analytical skills for a senior audience,