You will get a Machine Learning Project
Project details
Hello,
I work in Data Analysis and Machine Learning. I use python and pandas for finding hidden patterns in data and use graphing libraries to present the insights into graphical form. I can do all types of classification and regression models.
Libraries I usually use:
python pandas
stats module
Numpy
Scipy
sk-learn
Seaborn
Matplotlib
Not limited to these only
Machine Learning Models I can prepare for Classification:
K-Nearest Neighbors.
Naive Bayes
Logistic Regression
decision Tree Classifier
Random Forrest Classifier
Ridge Classifier
Support vector machine Classifier
Gradient Boosting Classifier
Linear Discriminant Analysis
OneVsOne Classifier
MultiOutput Classifier
GaussianNB
Stochastic Gradient Descent Classifier
Not limited to these only
Machine Learning Models I can prepare for Regression:
Linear Regression
Ridge Regression
LASSO Linear Regression
Elastic Net Regression
decision Tree Regression
Random Forrest Regression
K-Nearest Neighbors.Regression
Support vector machine Regression
Ridge Regression
Lasso Regression
Not limited to these only
Model validation, testing, regularization, hyperparameters, model documentation, etc.
Looking forward working with you!
I work in Data Analysis and Machine Learning. I use python and pandas for finding hidden patterns in data and use graphing libraries to present the insights into graphical form. I can do all types of classification and regression models.
Libraries I usually use:
python pandas
stats module
Numpy
Scipy
sk-learn
Seaborn
Matplotlib
Not limited to these only
Machine Learning Models I can prepare for Classification:
K-Nearest Neighbors.
Naive Bayes
Logistic Regression
decision Tree Classifier
Random Forrest Classifier
Ridge Classifier
Support vector machine Classifier
Gradient Boosting Classifier
Linear Discriminant Analysis
OneVsOne Classifier
MultiOutput Classifier
GaussianNB
Stochastic Gradient Descent Classifier
Not limited to these only
Machine Learning Models I can prepare for Regression:
Linear Regression
Ridge Regression
LASSO Linear Regression
Elastic Net Regression
decision Tree Regression
Random Forrest Regression
K-Nearest Neighbors.Regression
Support vector machine Regression
Ridge Regression
Lasso Regression
Not limited to these only
Model validation, testing, regularization, hyperparameters, model documentation, etc.
Looking forward working with you!
What's included
| Service Tiers |
Starter
$65
|
Standard
$120
|
Advanced
$200
|
|---|---|---|---|
| Delivery Time | 5 days | 7 days | 10 days |
Number of Revisions | Unlimited | Unlimited | Unlimited |
Number of Model Variations | 1 | 2 | 5 |
Number of Graphs/Charts | 5 | 10 | 15 |
Model Validation/Testing | - | ||
Model Documentation | - | ||
Data Source Connectivity | - | ||
Source Code | - | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$50
Additional Model Variation
(+ 1 Day)
+$50
Additional Scenario
(+ 1 Day)
+$50
Additional Graph/Chart
+$10
Model Validation/Testing
(+ 1 Day)
+$50
Model Documentation
(+ 1 Day)
+$30
Data Source Connectivity
+$40
Source Code
+$50About Nefrida
Data Scientist / Data Analyst / Python
Tirana, Albania - 3:06 am local time
I look forward to working with you.
Steps for completing your project
After purchasing the project, send requirements so Nefrida can start the project.
Delivery time starts when Nefrida receives requirements from you.
Nefrida works on your project following the steps below.
Revisions may occur after the delivery date.
Provide information
Please provide me information regarding the project!