Our Machine Learning Development Process
It's easy to get overwhelmed and feel that this may be too complex. Don't worry, we're here to help make it easy. Let's quickly go through the steps.
1. Scoping & Architecture Design
The first step begins with acquiring domain specific knowledge, understanding the problem, and identifying the opportunity. Based on the information gathered, we propose the technology stack best suited for the job.
2. Data Collection & Exploration
Machine learning needs data. If the data needed to train the proposed models exists, we conduct an exploratory analysis phase to find relevant patterns & correlations. If the data is not available, we work towards gathering it.
3. Model Development
Based on the information gathered thus far, we train, test & iterate upon thousands of models to see how accurately they are able to solve the problem statement. We continue to feed data and make tweaks as the models evolve.
4. Full-stack app development
Finally, we integrate the machine learning model with the front-end application using a REST API, developing all the required features along the way to provide an intuitive & user-friendly experience to the end user.