Why: AI Algorithm Evaluation
AI Models Architecture
We evaluate the architecture of the AI model to ensure it's suited for the problem it aims to solve. This involves checking layer types, activation functions, and hyperparameters to make sure they're all optimized for the task at hand.
Model Inferences
We check how the model serves inferences during runtime. This covers aspects like latency, throughput, and resource utilization to ensure that the model is efficient and scalable.
Data Cleaning
We assess how the raw data is cleaned to remove noise, outliers, and irrelevant information. This guarantees that the model is trained on high-quality data, improving its performance and reliability.
Missing Value Handling
Our team reviews the strategies implemented for handling missing data, from simple methods like mean imputation to more complex ones like model-based imputation, ensuring they're appropriate for the given context.
Exploratory Data Analysis (EDA)
We make sure EDA is thoroughly conducted and appropriately integrated into the codebase. This includes validating statistical tests, visualizations, and other techniques that give insight into the data's characteristics.
MLOps
We evaluate the MLOps procedures in place, like CI/CD pipelines, versioning, and monitoring, to make sure that the machine learning workflow is robust, maintainable, and in alignment with best practices.
Testimonials: What Our Clients Are Saying
Without their help, we may have gone out of business. We saw a 1,000% increase over the maximum capacity of our legacy systems, over 48,000 orders per day, and an average of 75 million page views and 2.3 million unique users each month in 2017.
Asif is a brilliant computer scientist, a physicist, an original thinker, an erudite scholar, and an artist who can sculpt new algorithms, and paint new solutions, veritably a Leonardo da Vinci of our times, and a passionate educator with deep insight into AI/ML/DL/Data-Science/Big-Data topics.
When it comes to Big-data and machine learning, I would simply say he (Asif) knows A-Z in that. No matter what the domain is, he has machine-learning-based solutions for the problems involved. Working with him for years, I have realized how his predictions on the machine learning revolution in big data have come true.
We’ve done development in the past..the SolutionMap is a higher level way of defining a comprehensive approach to getting the success that you want.
It was not just about software…it was all about what is this going to do in your company, how are the people in your organization with your partners and with your other stakeholders going to interact with this piece of software and what are their expectations of it…it also helped us on the backside thinking about our business processes…it was really illuminating to me.
From the design through to the development detail, they listened, understood, and carefully tested before release, often pushing our initial ideas to a better outcome.
