ML Engineer

github

Christine Straub  • Peerlist

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AI SQL Brain

The motivation was to experiment with end to end machine learning project and get some idea about deployment platform like Streamlit. By prior detection & through proper medical treatment, adverse effects can be prevented. To help in early detection, technology can be used very reliably and efficiently. Using machine learning we have built a predictive model that can predict whether the patient is diabetes positive or not.

Diabetes Detection Machine Learning Streamlit App

Medical Image and Signal Processing

Libraries: Tensorflow, Keras, Scipy, Sklearn, OpenCV, Pillow, CUDA, cudNN,SQL, Pandas, matplotlib

Stack:
- Deep knowledge in biomedical engineering- Analytical method and statistical analysis of medical image/signals.
- Machine learning for image analysis (CNN/DNN)
- SQL as well as NoSQL database technologies

Key Skill:
- Computer Vision (Object Recognition)
- Medical image analysis
- Large-scale image processing - 2d-filtering
- Quality Analysis Pipeline

Objective: Use cutting-edge computer vision and machine learning approach (tools and algorithms) to develop a powerful, low-cost, novel technology that combines the identification of bacterial infection with the determination of the most effective antibiotic to treat it, enabling results that currently take days in just life-saving hours.

Image(the sensor data) processing and analysis algorithm development are at the core of this job and the key tasks that were required to contribute are:

Accomplishments:

- Developed and implemented image processing algorithms to convert raw sensor signals into colorimetric time series data with the highest signal integrity.
- Developed and implemented vision-based quality control tools to be deployed at manufacturing (built and deployed the custom object detection CNN model).
- Developed tools to analyze and visualize high-volume, high-dimensional data to find interesting trends and correlations.
- Maintained image processing and data analysis software stack.
- Developed analytical methods and statistical analysis for processing high-volume, temporal high-dimensional data streams generated in real-time from proprietary sensor technology.
- Developed an algorithm for decisions and measurements of multi-dimensional data streams.
- Provided proper documentation of analyzed results.

Medical Image and Signal processing ML for SpecificDiagnosti

This application leverages OpenAI's powerful text-davinci-003 language model to convert natural language prompts into SQL statements. With this tool, you can easily translate your verbal instructions or queries into structured SQL commands.