You will get a jupyter notebook with data analysis and ml using python
Project details
Hello my name is Alexandre :)
I am an engineer with a Master's degree in Data Analysis and Machine Learning (UT Austin/Centrale). I use python, pandas and graphing libraries to explore data and showcase insights. I use models from sk-learn, keras and tensorflow to do classification and regression.
About my gig:
I usually use the following libraries:
python pandas
stats module
Numpy
Scipy
sk-learn
And many more !
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
And many more !
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
And many more !
I will be happy to discuss your projects with you !
I am an engineer with a Master's degree in Data Analysis and Machine Learning (UT Austin/Centrale). I use python, pandas and graphing libraries to explore data and showcase insights. I use models from sk-learn, keras and tensorflow to do classification and regression.
About my gig:
I usually use the following libraries:
python pandas
stats module
Numpy
Scipy
sk-learn
And many more !
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
And many more !
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
And many more !
I will be happy to discuss your projects with you !
What's included
| Service Tiers |
Starter
$5
|
Standard
$10
|
Advanced
$20
|
|---|---|---|---|
| Delivery Time | 1 day | 1 day | 2 days |
Number of Revisions | 1 | 2 | Unlimited |
Number of Model Variations | 1 | 2 | 4 |
Number of Scenarios | 1 | 1 | 2 |
Number of Graphs/Charts | 4 | 15 | 50 |
Model Validation/Testing | - | ||
Model Documentation | - | - | |
Data Source Connectivity | - | - | |
Source Code |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$20About Alex
Data scientist
New York City, United States - 3:57 pm local time
I am passionate about data science, mobile development and startups .
I had the opportunity to earn a Master's Degree in Science with a focus on Data analysis, worked in Europe, Singapore, New York and did research at the University of Texas at Austin.
My relationship and communication skills have been praised by my peers.
Feel free to contact me anytime, to talk about your AI/Machine learning projects, and mobile development !
Steps for completing your project
After purchasing the project, send requirements so Alex can start the project.
Delivery time starts when Alex receives requirements from you.
Alex works on your project following the steps below.
Revisions may occur after the delivery date.
data analysis
I will analyze the data. This step is the descriptive analysis of the data (mean, medians, variance, for example).