Segmenting AI, ML, DL and RPA
Artificial Intelligence (AI): a. Image Recognition: Identifying objects, people, and patterns in images. b. Natural Language Processing (NLP): Understanding and processing human language. c. Robotics: Developing intelligent machines capable of performing tasks autonomously. d. Expert Systems: Creating systems that mimic human decision-making processes.
Machine Learning (ML): a. Supervised Learning: Training models using labeled data to make predictions or classifications. b. Unsupervised Learning: Identifying patterns and relationships in data without labeled examples. c. Reinforcement Learning: Teaching models to make decisions based on feedback from their actions.
Deep Learning: a. Neural Networks: Building networks of interconnected nodes (neurons) to learn complex patterns. b. Convolutional Neural Networks (CNNs): Specialized for image recognition and processing. c. Recurrent Neural Networks (RNNs): Suitable for sequence data like text or time series.
Robotic Process Automation (RPA): a. Task Automation: Automating repetitive tasks such as data entry, form processing, and report generation. b. Workflow Automation: Streamlining business processes by integrating with various applications and systems. c. Cognitive Automation: Incorporating AI and ML to enable robots to learn and adapt to new tasks.