Hi and Welcome! This service aims to provide you with a solution based on machine learning with Python.

Do you have a dataset and do you want --- to analyze, process, model and report it --- in order to extract knowledge (for decision making for example)? If so, then this service provides you a Machine Learning (ML) solution modeled on the CRoss Industry Standard Process for Data Mining (CRISP-DM). CRISP-DM has 6 steps:

(S1) Understand the problem. Understand the objectives and requirements of the project, select the technologies used; examine data, its properties such as data format and number of records or field identities.

(S2) Understanding data. Exploratory Data Analysis (EDA): data visualization, analyze graphs from data visualization and Hypothesis tests if necessary;

(S3) Prepare data. Clean and format data; feature selection; feature engineering and features transformation or normalization;

(S4) Modeling. Generate a test design, perform a spot-check then select one model to solve your ML problem. The selected model will be part of one of the following learning types:
--- Supervised learning: linear regression and its variants, logistic regression, lda, qda, svm, decision tree, boosting algorithm, neural networks;
--- Unsupervised learning: centroid-based clustering, upper clustering, density-based and distribution-based clustering;
--- Dimension reduction: pca, svd, lda, embedding technique

(S5) Evaluation. Score the chosen model using a appropriate metric to the problem. Then review (1)-(4);

(S6) Deployment. Produce a final report, plan monitoring and maintenance, make the models operational;

The solution will be delivered as a .py or jupyter notebook.
Depending on your needs, this service offers the following options:


**************************** Basic Formula ($22.77) *****************************
--- Debugging a python machine learning script
(S1) Understand the problem
(S2) Understanding data. Only data visualization. No graph analysis and no hypothesis tests


******************************* Option 1 ($56.94) ********************************
(S1) Understand the problem
(S2) Understanding data


******************************* Option 2 ($68.32) *******************************
(S1) Understand the problem
(S2) Understanding data
(S3) Prepare data


******************************* Option 3 ( $91.10) ******************************
Add to Option (2) the steps (S4) and (S5)
(S4) Modeling.  Without the "model selection" part. One type of problem will be solved:
----- Regression problem or
----- Classification problem
(S5) Evaluation

******************************* Option 4 ( $113.87) *******************************
Add to Option (2) the steps (S4) and (S5)
(S4) Modeling. With the "model selection" part. One type of problem will be solved:
----- Regression problem or
----- Classification problem
(S5) Evaluation


******************************* Option 5 ( $113.87) *******************************
Add to Option (3) or Option (4) the step (S6)
(S6) Deployment. Write a final report.


Thank you.