According to MIT, Machine Learning is a subfield of artificial intelligence, which is broadly defined as the capability of a machine to imitate intelligent human behavior.
The main programming language used in machine learning is Python.
There are three main types of machine learning:
** Supervised Learning**
This is process where the training data has labels that guide the algorithm to build a model.
The process is known as predictive modeling i.e. making predictions sing data.
Some of the algorithms used include: Linear Regression, Logistic Regression, Decision Tree, Random forest and Naïve Bayes classifier.
Unsupervised learning
The data has no labels and are classified according to similarity in groups/ classes called clusters.
Key target is that similar objects belong to one group but different from objects in another group.
Some of the algorithms include: K-means clustering, Hierarchical clustering.
Reinforcement Learning
The model learns by interacting with an environment and is not taught. A RL agent learns from consequences of its actions on basis of past experiences (exploitation) and new choices (exploration).
Some of the libraries that are handful in machine learning are:
Scikit-learn: Used for data processing and implementing machine learning models.
https://medium.com/bootrain-blog/a-comprehensive-guide-to-scikit-learn-part-1-overview-of-the-package-b766f1da50daTensorFlow: An open source library that helps one to develop and train ML models.
https://www.tensorflow.org/Pytorch: An opensource ML framework that shapes the path from research prototyping to production deployment.
https://pytorch.org/Ensemble Models: a ML approach to combine other multiple models(base estimators) during prediction process.
https://towardsdatascience.com/ensemble-models-5a62d4f4cb0c
Machine Learning can be applied in many tasks such as:
- Fraud Detection
- Business Analysis and Automation
- Self Driving Cars
- Chat-bots to support Customer Service
- Market Research and Customer Segmentation
- Automated Security monitoring, among many others.
Learning and understanding Machine learning is a first step, rather a key to using data to create vast solutions.
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