Machine Learning is a field of computer science that uses statistical techniques to train a computer system to learn from data and act according to it. This field consists of many data-driven applications that are not explicitly programmed. We use this application to derive results from underlying data. These applications infer patterns and relationships between different variables in data sets. We can derive knowledge based on this relationship which helps to predict the outcome from the target data sets.
Machine learning allows us to analyze massive amounts of data. Though it takes some time to learn machine learning techniques initially, it brings many opportunities and profits to an organization when used properly.
Categories in Machine Learning
There are mainly four categories of machine learning.
- Supervised learning
- Unsupervised learning
- Reinforcement learning
- Semi-supervised learning
Use of Machine Learning in Real-world
Some applications and verticals use Machine Learning in real-time. Some of them are listed below.
- Video Game development
- Computer Vision
- Driverless Car
- Spam Filtering in Email
- Medical Diagnosis
- Image Recognition
- Time series forecasting
- Fraud Detection in Banks and Finance
- Sentiment analysis
- Financial market analysis
- Voice recognition
- Recommender systems for Movie, music, book, clothes, etc
Conclusion
We learned about machine learning its categories and the use of machine learning in real-world scenarios.
Please share this blog post on social media and leave a comment with any questions or suggestions.
References
