Machine learning is a subset of artificial intelligence, is a science of getting computers to act without being explicitly programmed. The global machine learning market is expected to grow from $7.3 billion in 2020 to $30.68 billion in 2024, which is CAGR of 43%.

It is based on the idea that machines can learn from the past information, identify patterns and make decisions using algorithms. There are three types of machine learning algorithms that are supervised learning, un-supervised learning and reinforcement learning.

We at smartData have professionals equipped with supervised learning capabilities to work with classification and regression problems. This includes speech recognition, drugs classification, biometric identification, image classification, face detection, sentiment analysis, classifying articles, medical data classifications, real-time predictions, etc. We are proficient in tools and libraries like TensorFlow, PyTorch, scikit-learn, regression models, classifier models, SVC, SVM, YOLO, Keras, etc.

Connect with us to know more about how we can transform your business through machine learning!

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FemTech- The Technology Shaping the Future of Women's Health

Women experience unique health issues whether it is Reproductive health, infertility, maternal health, post-natal depression, breast cancer, PCOD, menopause, etc. A proper guidance by advocating, evidence-based programs and community health, can avoid any life-threatening situation.

FemTech

What is Health Information Exchange(HIE)?

Electronic exchange of clinical information permits doctors, nurses, pharmacists, other health care providers, and patients to retrieve and securely share a patient's vital medical information electronically—improving the speed, quality, safety, coordination, and cost of patient care.

Health Information Exchange

Clinical Trials

COVID-19 has wreaked havoc throughout the country and the healthcare system. However, telemedicine is stepping up as the spotlight helping healthcare providers and caregivers better respond to the needs of the patients

Clinical Trials
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