ML Expert for Predictive Analysis
Budget: $30 – $250 USD
Looking for a proficient Machine Learning expert to tackle a task of prediction using Logistic regression, Random Forest, and K-Nearest techniques. My project's datasets are small with less than 1,000 data points, destined for an academic sector application.
Key Functionality:
- Implement Logistic Regression, Random Forest, and K-Nearest techniques
- Manage small-sized datasets effectively
- Understand academic sector applications
Ideal Skills and Experience:
- Extensive experience in ML predictive models
- Proficiency in Logistic Regression, Random Forest, and K-nearest techniques
- Understanding of ML models with small datasets
- Prior experience in academic sector projects is desirable.
Successful completion of this project requires a precise mix of technical knowledge, practical experience, and an innate understanding of academic project requirements. If you possess these qualities, your application is highly anticipated.
The project requirements are:
Data analysis:
Using the H1B Visa dataset and using Python:
- Data exploration: Explore the data and describe the dataset columns, data types, no. or rows
- Date pre-processing: List all applied data cleansing and pre-processing steps
- Data visualization: Provide charts for the main attributes
- Features selection Identify the candidate features to be used in the machine learning model
Machine learning :
- Use the dataset to build, train, and test machine learning models using the three techniques Logistic regression, Random forest, and K-Nearest.
- Measure the accuracy of each model
- Improve the model accuracy to reach 90%
- Document all improvement steps or factors used to improve the accuracy.
Integration:
- Use the highest accuracy model to develop a RESTFUL API that takes the applicant's details as JSON and returns whether he is approved or rejected in the response.
- Develop a data entry program to be used to enter the applicant details, call the API, and display the result on the screen
Provide the source code of all components and the related documentation.
The dataset is available here: https://www.kaggle.com/datasets/nsharan/h-1b-visa/
Below is a white paper describing the project idea.
https://www.kaggle.com/datasets/nsharan/h-1b-visa/
Key Functionality:
- Implement Logistic Regression, Random Forest, and K-Nearest techniques
- Manage small-sized datasets effectively
- Understand academic sector applications
Ideal Skills and Experience:
- Extensive experience in ML predictive models
- Proficiency in Logistic Regression, Random Forest, and K-nearest techniques
- Understanding of ML models with small datasets
- Prior experience in academic sector projects is desirable.
Successful completion of this project requires a precise mix of technical knowledge, practical experience, and an innate understanding of academic project requirements. If you possess these qualities, your application is highly anticipated.
The project requirements are:
Data analysis:
Using the H1B Visa dataset and using Python:
- Data exploration: Explore the data and describe the dataset columns, data types, no. or rows
- Date pre-processing: List all applied data cleansing and pre-processing steps
- Data visualization: Provide charts for the main attributes
- Features selection Identify the candidate features to be used in the machine learning model
Machine learning :
- Use the dataset to build, train, and test machine learning models using the three techniques Logistic regression, Random forest, and K-Nearest.
- Measure the accuracy of each model
- Improve the model accuracy to reach 90%
- Document all improvement steps or factors used to improve the accuracy.
Integration:
- Use the highest accuracy model to develop a RESTFUL API that takes the applicant's details as JSON and returns whether he is approved or rejected in the response.
- Develop a data entry program to be used to enter the applicant details, call the API, and display the result on the screen
Provide the source code of all components and the related documentation.
The dataset is available here: https://www.kaggle.com/datasets/nsharan/h-1b-visa/
Below is a white paper describing the project idea.
https://www.kaggle.com/datasets/nsharan/h-1b-visa/