PxPixel
Skip to content
Upwork home Log In
Project Catalog

You will get machine learning predictive models with analysis

Hanling W.
Hanling W.
4.8
This project $1500
  • Delivery Time 3 days
  • Number of Revisions 3
  • Number of Model Variations 6
    • Model Validation/Testing
    • Model Documentation
    • Data Source Connectivity
      -
    • Source Code
Upwork Payment Protection
Gives you security and peace of mind

Project details

You will get an analysis of how different machine learning predictive models perform on your dataset. With more than three years' experience in data science and predictive modeling, I purse to mine the gold from data and provide insights about how machine learning can help to boost your business. High quality work and 100% satisfaction!  
Tool scikit-learn

Project steps

  • 1
    Outline how the project would go on

  • 2
    Deliver models and analysis results

    Pre-process the dataset and provide ncessary data visualizations. Compare results from 6 models in scikit-learn (LR, SVM, DT, RF, GBDT, LightGBM), and show the feature importances. Analyze each model based on metrics and make a conclusion.

  • 3
    Necessary improvements

  • 4
    Final deliverables

    Include Jupyter Notebook (with HTML version), trained model files.

Requirements

  • 1
    Dataset to work with
  • 2
    Goal (what to predict based on what)
  • 3
    Other requirements (e.g., data pre-processing, deliverables)

About Hanling

Hanling W.
Machine Learning / Deep Learning Algorithm Engineer
Machine Learning / Deep Learning Algorithm Engineer
82% Job Success
Shenzhen, China - 10:54 am local time
I love discovering the myth under data! If you need any analysis on your data, feel free to let me know! My fields of interests: 1) Data Mining: Classification/Regression Tasks, Pattern Recognition, Data Analysis; 2) Computer Vision: Image Classification, Object Detection, Image Recognition, Deep Learning.

Skills:
------
✓ Solid background in Mathematics and statistics
✓ Skilled with data science tools, including Python, R, Matlab, Linux, MongoDB
✓ Skilled with deep learning framework, including Caffe, Tensorflow, Keras, PyTorch
✓ Familiar with machine learning algorithms, including LightGBM, XGBoost, RF, LR, FFM
✓ Familiar with various of NN architecture, including CNN (AlexNet, ResNet, GAN), RNN, DNN


Characteristics:
------------------
- Strong problem-solving skills
- Highly object/goal oriented
- Paying attention to details
- Easy to communicate

Your satisfaction is my drive!!!
 Â