Building your in-house Machine Learning team

ENBISYS coaches your team to get the most from your Data
Building your in-house Machine Learning team
ENBISYS coaches your team to get the most from your Data
Building your in-house Machine Learning team
ENBISYS coaches your team to get the most from your Data

Machine learning. Outstanding skill of the future

Machine Learning is powered by data and it has been the AI tool for extracting correlations, analyzing hidden patterns, and learning from data.
To capture value in the growing market of AI applications, companies are experimenting with different strategies, technologies, and opportunities, all of which require large investments.
A proprietary cloud-based machine learning solution can boost a company's productivity through identifying trends and providing insights into business processes, finances, offerings, and customers. It can also be used to automate some parts of day-to-day activities, replacing highly-qualified analytical or technical personnel.

As seen, the demand for Machine Learning skills is at all times high. Naturally, companies who own significant amounts of data – tend to establish their own Machine Learning teams.

Providing value and competitive advantages requires skilled workers, experts in converting data into valuable information through predictions obtained with the help of automatic learning systems.

Machine learning. Outstanding skill of the future

Machine Learning is powered by data and it has been the AI tool for extracting correlations, analyzing hidden patterns, and learning from data.
To capture value in the growing market of AI applications, companies are experimenting with different strategies, technologies, and opportunities, all of which require large investments.
A proprietary cloud-based machine learning solution can boost a company's productivity through identifying trends and providing insights into business processes, finances, offerings, and customers. It can also be used to automate some parts of day-to-day activities, replacing highly-qualified analytical or technical personnel.

As seen, the demand for Machine Learning skills is at all times high. Naturally, companies who own significant amounts of data – tend to establish their own Machine Learning teams.

Providing value and competitive advantages requires skilled workers, experts in converting data into valuable information through predictions obtained with the help of automatic learning systems.

Machine learning. Outstanding skill of the future

Machine Learning is powered by data and it has been the AI tool for extracting correlations, analyzing hidden patterns, and learning from data.
To capture value in the growing market of AI applications, companies are experimenting with different strategies, technologies, and opportunities, all of which require large investments.
A proprietary cloud-based machine learning solution can boost a company's productivity through identifying trends and providing insights into business processes, finances, offerings, and customers. It can also be used to automate some parts of day-to-day activities, replacing highly-qualified analytical or technical personnel.

As seen, the demand for Machine Learning skills is at all times high. Naturally, companies who own significant amounts of data – tend to establish their own Machine Learning teams.

Providing value and competitive advantages requires skilled workers, experts in converting data into valuable information through predictions obtained with the help of automatic learning systems.

Building your in-house ML lab

At ENBISYS we've established and grown our ML Department back in 2016, building a team of top-rank Data Engineers. We used the acquired capabilities to develop a number of own ML projects as well as projects for our clients, involving neural networks architecture and ML algorithms development in Healthcare, Education, Retail, Oil & Gas.

Building your in-house ML lab

At ENBISYS we've established and grown our ML Department back in 2016, building a team of top-rank Data Engineers. We used the acquired capabilities to develop a number of own ML projects as well as projects for our clients, involving neural networks architecture and ML algorithms development in Healthcare, Education, Retail, Oil & Gas.

Building your in-house ML lab

At ENBISYS we've established and grown our ML Department back in 2016, building a team of top-rank Data Engineers. We used the acquired capabilities to develop a number of own ML projects as well as projects for our clients, involving neural networks architecture and ML algorithms development in Healthcare, Education, Retail, Oil & Gas.

We see the task of growing an in-house ML team as a logical strategy for any company that plans to grow. And we're here to help you in exploring possible solutions of how ML can be beneficial for your business.
We see the task of growing an in-house ML team as a logical strategy for any company that plans to grow. And we're here to help you in exploring possible solutions of how ML can be beneficial for your business.
We see the task of growing an in-house ML team as a logical strategy for any company that plans to grow. And we're here to help you in exploring possible solutions of how ML can be beneficial for your business.

Possible machine learning LAB construction scenario

Possible machine learning LAB construction scenario

Possible machine learning LAB construction scenario

Scenario 1
Scenario 2
Scenario 3
Scenario 4
Scenario 5
Safe
Takes too long
No commercial projects
High costs
Grow the team from own data engineers
Fast established team
High costs
Hire experienced
Data Scientists
+ Commercial project
No control over ML Team's work due to lack of competencies internally
Risk of failing the project
Methodology
Theory base for technology stacks
Learn through courses available
Difficult to implement acquired theory to real life projects
No clear strategy for ML projects
Fast established team
No risk for the project

Almost impossible to source such experts
Difficult to assess the candidate
Hire CDO/CDS
Speeds up Option 1 dramatically
Dedicate/Hire junior
Data Scientists
+ Commercial Project
+ ENBISYS ML Consultants
team

When a company decides to set up its own ML team and deliver commercial projects, it's important to manage expectations.

Since ML is not yet a mature technology, it doesn't just work "out of the box". Every model is unique and must be trained, which involves a lot of experimenting. The process requires substantial inputs in the form of computational resources, data, and manpower. Algorithms may be making assessments, predictions, and recommendations, but a human touch is essential to the initial set up to oversee and act on any outputs.

Setting up a Data Science Team means that the team members need to have experience in computer science, mathematics, as well as relevant domain expertise.

The decision to build a Machine Learning team is serious and once taken, ENBISYS can provide support and recommendations to run this process smoothly and efficiently.

When a company decides to set up its own ML team and deliver commercial projects, it's important to manage expectations.

Since ML is not yet a mature technology, it doesn't just work "out of the box". Every model is unique and must be trained, which involves a lot of experimenting. The process requires substantial inputs in the form of computational resources, data, and manpower. Algorithms may be making assessments, predictions, and recommendations, but a human touch is essential to the initial set up to oversee and act on any outputs.

Setting up a Data Science Team means that the team members need to have experience in computer science, mathematics, as well as relevant domain expertise.

The decision to build a Machine Learning team is serious and once taken, ENBISYS can provide support and recommendations to run this process smoothly and efficiently.

When a company decides to set up its own ML team and deliver commercial projects, it's important to manage expectations.

Since ML is not yet a mature technology, it doesn't just work "out of the box". Every model is unique and must be trained, which involves a lot of experimenting. The process requires substantial inputs in the form of computational resources, data, and manpower. Algorithms may be making assessments, predictions, and recommendations, but a human touch is essential to the initial set up to oversee and act on any outputs.

Setting up a Data Science Team means that the team members need to have experience in computer science, mathematics, as well as relevant domain expertise.

The decision to build a Machine Learning team is serious and once taken, ENBISYS can provide support and recommendations to run this process smoothly and efficiently.

What you'll get

Forward-looking
Companies already investing in related technology are more likely to invest in AI and Machine Learning
Resources available
Tech giants and digital-native companies, big corporations
Creative
Companies are using AI for product and service innovation, not just to automate repetitive, rules-based processes
Focused
The AI investment is linked to the company's core business, it's more than a case of exploring an interesting side road of the company's journey
Broad scope
Early adopters do not specialize in just one type of technology. They use multiple AI tools for various needs
Committed
There is strong pro-AI leadership at the C-suite level

What you'll get

Forward-looking
Companies already investing in related technology are more likely to invest in AI and Machine Learning
Resources available
Tech giants and digital-native companies, big corporations
Creative
Companies are using AI for product and service innovation, not just to automate repetitive, rules-based processes
Focused
The AI investment is linked to the company's core business, it's more than a case of exploring an interesting side road of the company's journey
Broad scope
Early adopters do not specialize in just one type of technology. They use multiple AI tools for various needs
Committed
There is strong pro-AI leadership at the C-suite level

What you'll get

Forward-looking
Companies already investing in related technology are more likely to invest in AI and Machine Learning
Resources available
Tech giants and digital-native companies, big corporations
Creative
Companies are using AI for product and service innovation, not just to automate repetitive, rules-based processes
Focused
The AI investment is linked to the company's core business, it's more than a case of exploring an interesting side road of the company's journey
Broad scope
Early adopters do not specialize in just one type of technology. They use multiple AI tools for various needs
Committed
There is strong pro-AI leadership at the C-suite level

ENBISYS Team

Since applying Machine Learning to existing projects requires knowledge, skills, and experience in various domains, we configured the cross-functional team capable of crafting the Machine Learning projects fast and with scalability in mind. Our experienced Solution Architects, Data Scientists, ML Engineers, Frontend developers, Backend developers, DevOps, UI/UX, QAE, and our very own CDS are key to our ML initiative success.
ENBISYS invests heavily in the equipment to perform ML research: suitable GPUs and Cloud capacities are our common spending since the Data Science team is only as good as the company's equipment.

ENBISYS Team

Since applying Machine Learning to existing projects requires knowledge, skills, and experience in various domains, we configured the cross-functional team capable of crafting the Machine Learning projects fast and with scalability in mind. Our experienced Solution Architects, Data Scientists, ML Engineers, Frontend developers, Backend developers, DevOps, UI/UX, QAE, and our very own CDS are key to our ML initiative success.
ENBISYS invests heavily in the equipment to perform ML research: suitable GPUs and Cloud capacities are our common spending since the Data Science team is only as good as the company's equipment.

ENBISYS Team

Since applying Machine Learning to existing projects requires knowledge, skills, and experience in various domains, we configured the cross-functional team capable of crafting the Machine Learning projects fast and with scalability in mind. Our experienced Solution Architects, Data Scientists, ML Engineers, Frontend developers, Backend developers, DevOps, UI/UX, QAE, and our very own CDS are key to our ML initiative success.
ENBISYS invests heavily in the equipment to perform ML research: suitable GPUs and Cloud capacities are our common spending since the Data Science team is only as good as the company's equipment.

ENBISYS Machine Learning Skills

Deep Learning
Spatial Networks And Spatial Analysis
Neural Networks Assembling
Image recognition
Decision Trees
Predictive analytics
System integrations
Stochastic algorithms
AR apps development
API development
Bayesian Knowledge Tracing (BKT) algorithms modifications
Python/R Development

ENBISYS Machine Learning Skills

Deep Learning
Spatial Networks And Spatial Analysis
Neural Networks Assembling
Image recognition
Decision Trees
Predictive analytics
System integrations
Stochastic algorithms
AR apps development
API development
Bayesian Knowledge Tracing (BKT) algorithms modifications
Python/R Development

ENBISYS Machine Learning Skills

Deep Learning
Spatial Networks And Spatial Analysis
Neural Networks Assembling
Image recognition
Decision Trees
Predictive analytics
System integrations
Stochastic algorithms
AR apps development
API development
Bayesian Knowledge Tracing (BKT) algorithms modifications
Python/R Development

What we suggest

What we suggest

What we suggest

The most effective AI technique nowadays is Machine Learning which includes Deep Learning, Clustering, Bayesian Networks, and other approaches.

At ENBISYS AI Research, we cultivate specific scientific methods such as algorithms set to prepare clean data, train neural networks, and integrate outputs into the Clients' solutions.
The most effective AI technique nowadays is Machine Learning which includes Deep Learning, Clustering, Bayesian Networks, and other approaches.

At ENBISYS AI Research, we cultivate specific scientific methods such as algorithms set to prepare clean data, train neural networks, and integrate outputs into the Clients' solutions.
The most effective AI technique nowadays is Machine Learning which includes Deep Learning, Clustering, Bayesian Networks, and other approaches.

At ENBISYS AI Research, we cultivate specific scientific methods such as algorithms set to prepare clean data, train neural networks, and integrate outputs into the Clients' solutions.
We know how to customize Machine Learning for each specific business goal, whether that be Predictive Analytics, Enhanced Performance or BI - ENBISYS crafts the right strategy for your solution
We know how to customize Machine Learning for each specific business goal, whether that be Predictive Analytics, Enhanced Performance or BI - ENBISYS crafts the right strategy for your solution
We know how to customize Machine Learning for each specific business goal, whether that be Predictive Analytics, Enhanced Performance or BI - ENBISYS crafts the right strategy for your solution
To build your in-house Machine Learning team, we will dedicate 2 Data Scientists and/or CDS to explore your objectives and craft a customized strategy. We will work closely with your team to transfer the right methodologies and technical skills and support you with your first commercial ML projects.

Get the most pertinent expertise from ENBISYS, and projects requiring integrated Machine Learning solutions will become your revenue drivers very soon!

In each specific case, we offer the most optimal combination of approaches to reach the goal of our Client.

To build your in-house Machine Learning team, we will dedicate 2 Data Scientists and/or CDS to explore your objectives and craft a customized strategy. We will work closely with your team to transfer the right methodologies and technical skills and support you with your first commercial ML projects.

Get the most pertinent expertise from ENBISYS, and projects requiring integrated Machine Learning solutions will become your revenue drivers very soon!

In each specific case, we offer the most optimal combination of approaches to reach the goal of our Client.

To build your in-house Machine Learning team, we will dedicate 2 Data Scientists and/or CDS to explore your objectives and craft a customized strategy. We will work closely with your team to transfer the right methodologies and technical skills and support you with your first commercial ML projects.

Get the most pertinent expertise from ENBISYS, and projects requiring integrated Machine Learning solutions will become your revenue drivers very soon!

In each specific case, we offer the most optimal combination of approaches to reach the goal of our Client.

Let's start a new Machine Learning project together!

you agree to our Privacy Policy and Terms of Service

Let's start a new Machine Learning project together!

you agree to our Privacy Policy and Terms of Service

Let's start a new Machine Learning project together!

you agree to our Privacy Policy and Terms of Service