Machine Learning is revolutionizing every industry that we come across in our day-to-day life. Deep testing of ML tools acts as a catalyst, for easy implementation in these fields. Top latest trends in Machine Learning are:
- Auto ML: Automated Machine Learning is to automate the machine learning process itself. The Main function of this algorithm is to build & deploy ML models.
- Deep Learning: This involves building neural networks with layers to solve complex problems such as – image recognition, speech recognition, language processing, etc.
- Cyber Security: With changing Cyber attack patterns, ML algorithms are also getting improved with time. Hence, such algorithms have capability to recognize and tackle new attack patterns.
- Knowledge Transfer: It uses predefined models and utilizes them for new tasks. This can save time and resources by reducing the need for training models from scratch.
- Generative ML models: These models are used to generate a new database that is similar to an existing database. Such models are being used to generate numerous types of data like – text, images, and music.
- No-Code ML: It is a way of programming where there is no need to go through a long & cumbersome process of designing, collecting sample data, training, deployment, etc.
- Reinforcement Learning: It involves learning based on performing certain actions and learning from them. Such models are used in automotive industries like – self-driven cars, gaming, etc. The principal feature of such algorithms is safer & self-reinforcing learning systems.
- Explainable ML Models: With the increasing use of ML models, demand for making explainable models has also increased. This aims to develop and design techniques that can help humans understand how AI models make decisions.
- ML Operation Management (MLOps): The main purpose of creating these algorithms is to improve efficiency and productivity. Algorithms with the potential to integrate the development & deployment of systems into a single process are created.