Machine learning & Deep learning
Machine learning and deep learning are two branches of artificial intelligence that have revolutionized the field of data analysis and predictive modeling. Machine learning algorithms allow computers to learn from data and make predictions or decisions without being explicitly programmed. Deep learning is a subset of machine learning that uses neural networks with many layers to extract features from data and make more accurate predictions. Both techniques are widely used in businesses across various fields such as healthcare, finance, e-commerce, and marketing. For instance, in healthcare, machine learning is used to analyze medical images and diagnose diseases, while in finance, it is used for fraud detection and risk analysis. Similarly, deep learning is used in speech recognition, natural language processing, and image recognition. In summary, machine learning and deep learning offer significant benefits to businesses by enabling them to automate and optimize their operations, improve customer experience, and make more informed decisions.
Goal
Help businesses leverage the power of machine learning and deep learning to gain insights, automate processes, and improve decision-making.
Approach
Our approach involves understanding the business problem at hand, identifying the most suitable machine learning or deep learning algorithms, and developing custom models that deliver actionable insights. We work closely with our clients to ensure that our solutions are aligned with their business objectives and provide measurable results.
Results
By working with us, businesses can expect to see significant improvements in their operations, customer experience, and bottom line. Our solutions can help businesses optimize their marketing campaigns, reduce costs, improve efficiency, and identify new revenue streams. Additionally, our machine learning and deep learning models can help businesses make more informed decisions by providing predictive insights that allow them to anticipate market trends, identify customer needs, and improve overall business performance. Overall, our goal is to help businesses unlock the full potential of machine learning and deep learning to drive growth and success.
USE CASE EXAMPLE
The COVID-19 pandemic has caused a significant shift in global health practices, with the use of face masks becoming increasingly common in public settings. We developed a deep learning model for face mask detection that allows to assess mask adherence policies.
This was accomplished by fine-tuning a pre-trained VGG16 convolutional neural network on a dataset of 7553 RGB images of faces with and without masks. The final classification layer of the VGG16 model was modified to output two classes corresponding to the presence or absence of a mask. The model was also trained using cross-entropy loss and optimized using the Adam optimizer.
The face mask detection model achieved high accuracy, with a final accuracy of 99.8% on the test set. The model was able to successfully distinguish between faces with masks and without masks, providing a valuable tool for monitoring compliance with face mask mandates. This project demonstrates the effectiveness of deep learning techniques for image classification tasks and the importance of fine-tuning pre-trained models for improved accuracy.
The full workflow as well as the model itself can be found on Github.
About.
At our core, we believe that data is one of the most valuable assets a company can have. Our experience in using data analytics and machine learning can unlock novel insights, helping our clients make informed decisions that can drive business success.
Our expertise extends across a variety of industries, including healthcare, finance, e-commerce, and more. With a tailored approach, we aim to meet the unique needs and goals of each client, whether this is a small startup or a large enterprise.