Machine Learning Team Training and Consulting
Train your engineers to create ML algorithms
Machine Learning Team Training and Consulting
Train your engineers to create ML algorithms
Machine Learning Team Training and Consulting
Train your engineers to create ML algorithms
The Client
Sakhalin Energy, Russia
Production, transportation, processing, and marketing of oil and natural gas.
Production, transportation, processing, and marketing of oil and natural gas.
The Client
Sakhalin Energy, Russia
Production, transportation, processing, and marketing of oil and natural gas.
Production, transportation, processing, and marketing of oil and natural gas.
The Client
Sakhalin Energy, Russia
Production, transportation, processing, and marketing of oil and natural gas.
Production, transportation, processing, and marketing of oil and natural gas.
Python, SciKitLearn/Pandas, Pytorch, VAE (1D-CNN/LSTM/GRU), TensorBoard
Python, SciKitLearn/Pandas, Pytorch, VAE (1D-CNN/LSTM/GRU), TensorBoard
Python, SciKitLearn/Pandas, Pytorch, VAE (1D-CNN/LSTM/GRU), TensorBoard
Challenge
Challenge
Challenge
The Client has accumulated large amounts of proprietary data that can be used to build smart ML algorithms. They established a dedicated Data Science Department consisting of four subject matter experts and two recent graduates. The key objective of this subdivision was to set up a system that can detect early signs of equipment degradation well before it becomes critical.
The Client has accumulated large amounts of proprietary data that can be used to build smart ML algorithms. They established a dedicated Data Science Department consisting of four subject matter experts and two recent graduates. The key objective of this subdivision was to set up a system that can detect early signs of equipment degradation well before it becomes critical.
The Client has accumulated large amounts of proprietary data that can be used to build smart ML algorithms. They established a dedicated Data Science Department consisting of four subject matter experts and two recent graduates. The key objective of this subdivision was to set up a system that can detect early signs of equipment degradation well before it becomes critical.
The Company needed to boost the analytical skills of their junior specialists so that they can independently work on analytics cases. ENBISYS team was invited to run a short intensive training program with little theory and maximum practical exercises.
The Company needed to boost the analytical skills of their junior specialists so that they can independently work on analytics cases. ENBISYS team was invited to run a short intensive training program with little theory and maximum practical exercises.
The Company needed to boost the analytical skills of their junior specialists so that they can independently work on analytics cases. ENBISYS team was invited to run a short intensive training program with little theory and maximum practical exercises.
Approach
Approach
Approach
ENBISYS provided the general course curriculum and the Client shared a number of problems to be reviewed. Then the agenda was adjusted to meet the Client's expectations to tackle the challenges in a more efficient manner.
Two ENBISYS Data Scientists stayed on the Client's premises for two months to deliver the training course and work on the company's cases.
Two ENBISYS Data Scientists stayed on the Client's premises for two months to deliver the training course and work on the company's cases.
ENBISYS provided the general course curriculum and the Client shared a number of problems to be reviewed. Then the agenda was adjusted to meet the Client's expectations to tackle the challenges in a more efficient manner.
Two ENBISYS Data Scientists stayed on the Client's premises for two months to deliver the training course and work on the company's cases.
Two ENBISYS Data Scientists stayed on the Client's premises for two months to deliver the training course and work on the company's cases.
ENBISYS provided the general course curriculum and the Client shared a number of problems to be reviewed. Then the agenda was adjusted to meet the Client's expectations to tackle the challenges in a more efficient manner.
Two ENBISYS Data Scientists stayed on the Client's premises for two months to deliver the training course and work on the company's cases.
Two ENBISYS Data Scientists stayed on the Client's premises for two months to deliver the training course and work on the company's cases.
Curriculum themes:
Python
Decision trees
NumPy
Artificial Neural
Pandas
Networks
Classification tasks
Regressions
Creating and training neural networks in Keras
Curriculum themes:
Python
Decision trees
NumPy
Artificial Neural
Pandas
Networks
Classification tasks
Regressions
Creating and training neural networks in Keras
Solution
During the course, the trainees practiced solving real Company's challenges under the guidance of experienced ENBISYS mentors. As a result, two models were created.
Solution
During the course, the trainees practiced solving real Company's challenges under the guidance of experienced ENBISYS mentors. As a result, two models were created.
Solution
During the course, the trainees practiced solving real Company's challenges under the guidance of experienced ENBISYS mentors. As a result, two models were created.
Model 1 is a predictive analytics solution. The team leveraged the data to develop a predictive analytics tool that would point to valves showing high degradation signs.
Model 2 is a Computer Vision solution. An operator in the field who's visually controlling the performance of the flare can accidentally miss a certain behavior of the flare which can result in flare tip damage and plant shut down. This leads to tremendous losses in idle time. The algorithm developed helps alert the operator when undesired flare behavior is possible so he could take action.
Model 2 is a Computer Vision solution. An operator in the field who's visually controlling the performance of the flare can accidentally miss a certain behavior of the flare which can result in flare tip damage and plant shut down. This leads to tremendous losses in idle time. The algorithm developed helps alert the operator when undesired flare behavior is possible so he could take action.
Model 1 is a predictive analytics solution. The team leveraged the data to develop a predictive analytics tool that would point to valves showing high degradation signs.
Model 2 is a Computer Vision solution. An operator in the field who's visually controlling the performance of the flare can accidentally miss a certain behavior of the flare which can result in flare tip damage and plant shut down. This leads to tremendous losses in idle time. The algorithm developed helps alert the operator when undesired flare behavior is possible so he could take action.
Model 2 is a Computer Vision solution. An operator in the field who's visually controlling the performance of the flare can accidentally miss a certain behavior of the flare which can result in flare tip damage and plant shut down. This leads to tremendous losses in idle time. The algorithm developed helps alert the operator when undesired flare behavior is possible so he could take action.
Model 1 is a predictive analytics solution. The team leveraged the data to develop a predictive analytics tool that would point to valves showing high degradation signs.
Model 2 is a Computer Vision solution. An operator in the field who's visually controlling the performance of the flare can accidentally miss a certain behavior of the flare which can result in flare tip damage and plant shut down. This leads to tremendous losses in idle time. The algorithm developed helps alert the operator when undesired flare behavior is possible so he could take action.
Model 2 is a Computer Vision solution. An operator in the field who's visually controlling the performance of the flare can accidentally miss a certain behavior of the flare which can result in flare tip damage and plant shut down. This leads to tremendous losses in idle time. The algorithm developed helps alert the operator when undesired flare behavior is possible so he could take action.
Client's Reviews
We certainly achieved our goal. We received a solid overview of Data Science and Machine Learning tools for problem-solving and tried most of them in practice.
Client's Reviews
We certainly achieved our goal. We received a solid overview of Data Science and Machine Learning tools for problem-solving and tried most of them in practice.
Client's Reviews
We certainly achieved our goal. We received a solid overview of Data Science and Machine Learning tools for problem-solving and tried most of them in practice.
Let's discuss your Case!
you agree to our Privacy Policy and Terms of Service
Let's discuss your Case!
you agree to our Privacy Policy and Terms of Service
Let's discuss your Case!
you agree to our Privacy Policy and Terms of Service
SERVICES
VERTICALS
COMPANY
Tomsk, Russia, 634055,
Akademichesky prospekt, 8/8, of.502
info@enbisys.com
Akademichesky prospekt, 8/8, of.502
info@enbisys.com
© 2006-2023 Enbisys
Eve Krasnova
CBDO
e.krasnova@enbisys.com
CASES
AI RESEARCH