Machine Learning
Consulting Partners.
Embrace data challenges by building Machine Learning applications to improve business operations as a key component of digital strategy and decision making.
Krasamo is a Machine Learning development company with proven experience in building successful ML-based products.
Krasamo’s Machine Learning
Consulting Services
As a qualified collaborative partner with a decade of experience and proven expertise in Machine Learning consulting and development, Krasamo can design and build your Machine Learning applications.
Krasamo offers:
1. Data Services.
We implement tools to label and prepare data workflows, selection, cleansing, exploration, bias, robustness, visualization, and processing. We build infrastructure and automation to capture, maintain, and audit data—as well as develop ETL/ELT solutions to leverage existing data.
2. ML Models and Applications.
3. Platform Solutions.
We develop (code) solutions to access trained models to enable prediction capabilities from existing applications.
We integrate your apps to data platforms and tools to prepare data to train ML learning models with end-to-end visualization.
4. Consulting Services.
Selecting Algorithms
How to choose the best Machine Learning algorithm?
At Krasamo, we apply techniques to identify and pick the algorithms according to their properties, the type of problem, and the existing data. Once we have the data, we fit the algorithm to the data using parameter sets until obtaining acceptable predictions.
It is best to start with simple algorithms while the data is being collected. We test several algorithms and models until we reach validation. Also, we apply visualization methods, check training time, and analyze results to determine if the ML solution makes sense.
Contact our Machine Learning consulting engineers to discuss this topic further.
Development of Machine
Learning Systems
Agile best practices for software development are also used for ML system development, but ML applications present challenges that require extra efforts due to the complexity of their components.
The ML development process takes longer to build and to reproduce, as it requires many iterations exploring data, algorithms, and training, as well as testing ML models. It requires building a data pipeline—a manual process that gradually becomes semiautomated or fully automated. Data pipelines transform the data during training and prediction. As inputs change, data needs to be retrained to feed the model and avoid degradation.
Download our eBook about building Machine Learning models:
Developing ML systems and components requires skilled teams who know how to apply the right techniques and combinations of tools, workflows, monitoring, data science, and engineering synergies to achieve scalability.
Leading Machine
Learning Frameworks
Create a Proof of Concept (PoC) with Krasamo
We will work with your enterprise to check the technical and economic feasibility of adding Machine Learning to your systems. We’ll help you uncover roadblocks as well as develop insights about scope, costs, timeline, and risks.
Integrate Your ML Applications
with Third-Party Services
Our teams can help your company develop the capabilities to prepare, build, train, and deploy machine learning models using third-party cloud services to speed up the development of custom applications and MLOps environments.
Krasamo recommends major cloud platforms that offer Machine Learning capabilities and infrastructure, such as an integrated development environment (IDE), framework support, workflow orchestration, data automation, monitoring, security, etc.
Machine Learning Challenges (Pain Points)
- Developing ML Systems and Apps
- Building Machine Learning Models
- Building ETL Pipelines
- Performing Data Cleaning
- Executing Infrastructure Management
- Implementing Machine Learning Automation
Based in Dallas, Texas, and serving customers throughout the US, Krasamo is an experienced software developer offering Machine Learning consulting services and development.
Check out these articles for more information!
What is Machine Learning?
ETL Pipelines and Data Strategy Overview
Building Machine Learning Models Overview