You will get Machine learning model for any problem related to data
Project details
Here are the key points you'll get in the project:
1. Detailed report analysis of your machine learning model.
2. Justification of your problem statement in the live meeting.
3. Well-documented notebook.
4. Model deployment document will be provided.
1. Detailed report analysis of your machine learning model.
2. Justification of your problem statement in the live meeting.
3. Well-documented notebook.
4. Model deployment document will be provided.
What's included $100
These options are included with the project scope.
$100
- Delivery Time 9 days
- Number of Revisions 3
- Number of Model Variations 3
- Number of Scenarios 1
- Number of Graphs/Charts 3
- Model Validation/Testing
- Model Documentation
- Data Source Connectivity
- Source Code
Optional add-ons
You can add these on the next page.
Fast 6 Days Delivery
+$45
Additional Scenario
(+ 3 Days)
+$50About Arpit R
Data Scientist, Machine learning engineer
Noida, India - 4:47 am local time
1. Diligent Professional with 7+ years of experience in Data Science in wide functions including predictive modeling ,
data preprocessing, feature engineering, machine learning, and deep learning .; worked for tier- 1 customers from
various industry sectors like banking, insurance, stock brokerage rms, FMCG, pharmaceuticals, and PR agencies, and so
forth. 2. Improving products and services for clients by using advanced analytics, standing up big-data analytical tools ,
creating and maintaining models , and onboarding compelling new data sets.
3. Proficient in Python Stack, Exploratory Data Analysis, Statistics .
4. Improved Accuracy of the Document processing model by 40% by Implementing pdf processing techniques.
Steps for completing your project
After purchasing the project, send requirements so Arpit R can start the project.
Delivery time starts when Arpit R receives requirements from you.
Arpit R works on your project following the steps below.
Revisions may occur after the delivery date.
EDA
In this step, we'll complete data analysis.
Data Cleaning
In this step we'll prepare for data for training process.