We make
Data Science
look easy.

Berina Avdić

Senior Data Analyst @Atlantbh

Meet Berina and other Atlanters>
SERVICES

Data Science

We provide full-service Artificial Intelligence, conventional Machine Learning & Deep Learning development, as well as expertise in all the latest Data Science trends. Using expertise in Natural Language Processing (NLP) we can help your business understand all kinds of unstructured data and give you insights into what your data can tell you. Our team can provide a full range of data services from data acquisition, preparation, transformation to creating a data product. In a nutshell, we will create a custom made Data Science solution for your business needs.

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Technology stack

We use a wide range of analytics and Data Science tools, technologies and languages to help you extract insights and value from data, including; Supervised & Unsupervised Learning, NLP, Data Storytelling, Machine Learning, Data Mining and more.

client
client
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Python

What we do

Our full-stack Data Science services provide you with an end-to-end, flexible process resulting in solutions for your business decision-making needs and supported by your data. Using the power of machine learning we will automate and augment your processes, boosting your business results.

  • Prescription and optimization
  • Data extraction
  • Data verification
  • Data categorization
  • Business intelligence
  • Data analysis services
  • Data capture
  • Data visualization
  • Predictions and recommendations

How we do it

No unicorns or magic, just the latest Data Science trends and a whole lot of experience.

1

Translating Problems into Solutions

We begin by translating business problems into Data Science problems. We define the goals and metrics of the solution.
2

Proof Of Concept and Machine Learning

We then develop and execute a data strategy followed by the development of a Proof of Concept (PoC) solution. During this phase we might develop custom made machine learning models just for you, perform training and thorough model testing.
3

Data Product

After the PoC phase has met the defined goals, we will continue by developing a data product, involving all the steps of software product development and then some. At the same time, our Data Scientists will continue to improve and tune machine learning models, iteratively. After development is complete, we will continue to monitor and perform model updates.
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Blogs and Success Stories

Unleashing the Power of AI in Product Development, Samra TanovicData Science & AnalyticsProduct ManagementTop
July 24, 2023

Unleashing the Power of AI in Product Development

Lately, we have seen a significant number of discussions regarding the potential of AI and strategies to incorporate it into the product development process. Specifically, how can we enhance, innovate, and scale in ways we were not able to do before? In this interview, we asked Samra Tanovic, our VP…
Atlantbh 0
Love8
Clustering Algorithms: DBSCAN vs. OPTICSData Science & AnalyticsTech Bites
July 5, 2023

Clustering Algorithms: DBSCAN vs. OPTICS

Nowadays, we live in a world of data, which means we are constantly surrounded by enormous amounts of data. Data is generated by everything we do, both online and offline, from our internet activities and purchases to our physical motions and interactions. This data contains valuable insights and knowledge that…
Anja Plakalovic 0
Love15
Random String DetectionBlogData Science & Analytics
May 15, 2023

Random String Detection

What are Random Strings? Data analysis often presents us with the challenge of dealing with noisy inputs. This is particularly evident when working with large datasets of user inputs. Detecting and filtering out random string inputs can prove invaluable in various scenarios, such as data validation, quality control or the…
Mehmed Kadric 0
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Let's collaborate

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