Montclair University Data Science with Python
Project 3
After learning about Data Science in depth, it is now time to implement the knowledge gained through this course in real-life scenarios. We will provide you with four scenarios where you need to implement data science solutions. To perform these tasks, you can use the different Python libraries such as NumPy, SciPy, Pandas, scikit-learn, matplotlib, BeautifulSoup, and so on.
Perform a service request data analysis of New York City 311 calls. You will focus on the data wrangling techniques to understand the pattern in the data and also visualize the major complaint types.
Import a 311 NYC service request
Basic data exploratory analysis
Explore data
Find patterns
Display the complaint type and city together
Find major complaint types
Find the top 10 complaint types
Plot a bar graph of count vs. complaint types
Visualize the complaint types
Display the major complaint types and their count
The required resources for this project is available in Downloads section (Learning Tools > Downloads > Projects). Good Luck!
Project 04
Data Science with Python Real World Project
After learning about Data Science in depth, it is now time to implement the knowledge gained through this course in real-life scenarios. We will provide you with four scenarios where you need to implement data science solutions. To perform these tasks, you can use the different Python libraries such as NumPy, SciPy, Pandas, scikit-learn, matplotlib, BeautifulSoup, and so on.
Movielens Dataset Analysis
The GroupLens Research Project is a research group in the Department of Computer Science and Engineering in the University of Minnesota. The researchers of this group are involved in many research projects related to the fields of information filtering, collaborative filtering, and recommender systems. Here, we ask you to perform the analysis using the Exploratory Data Analysis technique. In particular, we want you to apply the tools of machine learning to predict the survivors of the tragedy.
The details of these projects and the scope of each project are listed in the sections below.
Data acquisition of the movielens dataset
Perform the Exploratory Data Analysis (EDA) for the users dataset
Perform machine learning on first 500 extracted records
Use the following features:
movie id
age
occupation
Use rating as label
Create train and test data set and perform the following:
users dataset
rating dataset
movies dataset
Visualize user age distribution
Visualize overall rating by users
Find and visualize the user rating of the movie “Toy Story”
Find and visualize the viewership of the movie “Toy Story” by age group
Find and visualize the top 25 movies by viewership rating
Find the rating for a particular user of user id = 2696
Create a histogram for movie, age, and occupation
The required resources for this project will be available in the Downloads section (Learning Tools > Downloads > Projects). Good Luck!
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