futureanalytica

  Machine Learning in Manufacturing Industry Machine Learning  is a part of Artificial Intelligence and is a process of training a computer that focuses on how we use data and algorithms to think like human beings. However, machine learning is not an easy process. With the use of statistical methods, algorithms are trained to make predictions or classifications, unveil key insights within data mining projects. These insights are important to make better decisions without being specifically programmed to do so. Machine Learning Model is built when you train your machine learning algorithms with data.  For example, a predictive algorithm will build a predictive model, when you provide data, and therefore, you will receive a model which is based on predictive model data. Before deployment machine learning enables models to train on data sets. These trained models can be used in real-time to learn from data. The improvements in accuracy level are a result of the training ...

  At  FutureAnalytica , we have optimized the lifecycle of 🏭 production lines to harness operational efficiency with superior automated No-Code AI/ML Algorithms. Keep track of 🏗 equipment’s uptime by analyzing structured data like equipment model, make and year, and unstructured data like log entries, ⚠️ error messages, and other factors. A not so faulty part or component can lead to inaccuracies, a high-cost deployment for manufacturers is no more a challenge. Uncover  #AI  transformation in the  #manufacturing  industry that will drive 🚀 profits and growth. 😎 Make smarter AI-driven Decisions. Request for free Demo 🖥️ and Get Connected at 👉  info@futureanalytica.com  |  https://bit.ly/3NRJPSo

  Did you know 🏭 Manufacturing is one of the main industries that use 🦾 AI & ML technologies to their fullest potential? As per the Google Trends report, people were searching for “AI in Manufacturing” in 2022 more than ever before. FutureAnalytica ’s AI Solutions for 🏗  Manufacturing  is most commonly applied in manufacturing to improve ⚙️🧰🛠 Overall Equipment Efficiency (OEE) and first-pass yield in production. Over time, manufacturers can use AI to increase uptime and improve quality & consistency, which allows for better forecasting. Request for free Demo 🖥️ and Get Connected at 👉  info@futureanalytica.com .

  The 🏢 organizations who understand the power of using their data, get profitable hidden insights for increasing business value, improving decision making, and growing their 💰 revenue, without much complexity. At  FutureAnalytica , we aim at empowering every business by automating complex Data using Data Science to 🎯 actionable insights. Reach out to us for free Demo 🖥️ and Get Connected at 👉  info@futureanalytica.com  |  https://lnkd.in/dxKPv-6d

  We all can take big or small actions to save 🌏 Mother Earth and raise awareness to protect the environment and biodiversity, Earth Day is celebrated each year on April 22. Keep the Earth ♻️ Clean and 🌳 Green to make a better World for All.

  Predictive Analytics in Healthcare Predictive Analytics:   Predictive analytics  is a part of advanced analytics in Artificial Intelligence that makes predictions about future results or forecast activity, behavior, and trends. With the use of historical and current data combined with data mining techniques, machine learning (ML), statistical modeling and superior AI/MLOps algorithm, we make faster decisions. Organizations or companies apply predictive analytics to find patterns in the data to identify risks and opportunities. With predictive analytics with the help of Data Science and Big Data, the healthcare sector can predict patient journeys with better solutions. In today’s world organizations and companies have to deal with enormous data, which is, received through different sources in the structured and unstructured form of images, video, sensors, transactional databases, equipment log files, and other data sources. To get meaningful insights from this data, stat...