Pinned Repositories
Automotive-Airfoil-Design
Automotive airfoil design app, powered by AeroSandbox and Dash
Basic-calculator-with-gui-and-python-Function
I have a basic calculator just for fun and python function practice .. I feel tkinter python is very easy to learn.. and fun..
Git_test_Hello
this repo made by just for testing prepose
IoT-For-Beginners
12 Weeks, 24 Lessons, IoT for All!
kirtesh1405
Config files for my GitHub profile.
ML_Project_1_Mercedes-Benz-Greener-Manufacturing
ML_Project_2_Income-Qualification
Project_1-Customer-Service-Requests-Analysis
Proejct Descrription:- You've been asked to perform data analysis of service request (311) calls from New York City. You've also been asked to utilize data wrangling techniques to understand the pattern in the data and visualize the major types of complaints.
Project_2_Customer-Service-Requests-Analysis
Project_3---Movielence_case_study
Project_3:- Movielence_case_study Background of Problem Statement : The GroupLens Research Project is a research group in the Department of Computer Science and Engineering at the University of Minnesota. Members of the GroupLens Research Project are involved in many research projects related to the fields of information filtering, collaborative filtering, and recommender systems. The project is led by professors John Riedl and Joseph Konstan. The project began to explore automated collaborative filtering in 1992 but is most well known for its worldwide trial of an automated collaborative filtering system for Usenet news in 1996. Since then the project has expanded its scope to research overall information by filtering solutions, integrating into content-based methods, as well as, improving current collaborative filtering technology. Problem Objective : Here, we ask you to perform the analysis using the Exploratory Data Analysis technique. You need to find features affecting the ratings of any particular movie and build a model to predict the movie ratings. Domain: Entertainment Analysis Tasks to be performed: Import the three datasets Create a new dataset [Master_Data] with the following columns MovieID Title UserID Age Gender Occupation Rating. (Hint: (i) Merge two tables at a time. (ii) Merge the tables using two primary keys MovieID & UserId)Explore the datasets using visual representations (graphs or tables), also include your comments on the following: User Age Distribution User rating of the movie “Toy Story” Top 25 movies by viewership rating Find the ratings for all the movies reviewed by for a particular user of user id = 2696 Feature Engineering: Use column genres: Find out all the unique genres (Hint: split the data in column genre making a list and then process the data to find out only the unique categories of genres) Create a separate column for each genre category with a one-hot encoding ( 1 and 0) whether or not the movie belongs to that genre. Determine the features affecting the ratings of any particular movie. Develop an appropriate model to predict the movie ratings
kirtesh1405's Repositories
kirtesh1405/Automotive-Airfoil-Design
Automotive airfoil design app, powered by AeroSandbox and Dash
kirtesh1405/Basic-calculator-with-gui-and-python-Function
I have a basic calculator just for fun and python function practice .. I feel tkinter python is very easy to learn.. and fun..
kirtesh1405/Git_test_Hello
this repo made by just for testing prepose
kirtesh1405/IoT-For-Beginners
12 Weeks, 24 Lessons, IoT for All!
kirtesh1405/kirtesh1405
Config files for my GitHub profile.
kirtesh1405/ML_Project_1_Mercedes-Benz-Greener-Manufacturing
kirtesh1405/ML_Project_2_Income-Qualification
kirtesh1405/Project_1-Customer-Service-Requests-Analysis
Proejct Descrription:- You've been asked to perform data analysis of service request (311) calls from New York City. You've also been asked to utilize data wrangling techniques to understand the pattern in the data and visualize the major types of complaints.
kirtesh1405/Project_2_Customer-Service-Requests-Analysis
kirtesh1405/Project_3---Movielence_case_study
Project_3:- Movielence_case_study Background of Problem Statement : The GroupLens Research Project is a research group in the Department of Computer Science and Engineering at the University of Minnesota. Members of the GroupLens Research Project are involved in many research projects related to the fields of information filtering, collaborative filtering, and recommender systems. The project is led by professors John Riedl and Joseph Konstan. The project began to explore automated collaborative filtering in 1992 but is most well known for its worldwide trial of an automated collaborative filtering system for Usenet news in 1996. Since then the project has expanded its scope to research overall information by filtering solutions, integrating into content-based methods, as well as, improving current collaborative filtering technology. Problem Objective : Here, we ask you to perform the analysis using the Exploratory Data Analysis technique. You need to find features affecting the ratings of any particular movie and build a model to predict the movie ratings. Domain: Entertainment Analysis Tasks to be performed: Import the three datasets Create a new dataset [Master_Data] with the following columns MovieID Title UserID Age Gender Occupation Rating. (Hint: (i) Merge two tables at a time. (ii) Merge the tables using two primary keys MovieID & UserId)Explore the datasets using visual representations (graphs or tables), also include your comments on the following: User Age Distribution User rating of the movie “Toy Story” Top 25 movies by viewership rating Find the ratings for all the movies reviewed by for a particular user of user id = 2696 Feature Engineering: Use column genres: Find out all the unique genres (Hint: split the data in column genre making a list and then process the data to find out only the unique categories of genres) Create a separate column for each genre category with a one-hot encoding ( 1 and 0) whether or not the movie belongs to that genre. Determine the features affecting the ratings of any particular movie. Develop an appropriate model to predict the movie ratings
kirtesh1405/streamlit-example
Example Streamlit app that you can fork to test out share.streamlit.io