The real apparition of the Machine Learning (ML) was in 1943 when Walter Pitts and Warren McCulloch created the first mathematical model of neural networks. “A logical Calculus of The Ideas Immanent in Nervous Activity”, has been used to create the algorithms that impact human thought processes. Nonetheless machine learning was limited and had no learning mechanism 

The AlphaGo algorithm is an event developed in March 2016 to highlight machine learning . It shocked the world by beating one of the best Go players, Lee Sedol. As it is a complex board game that requires strong intuition and abstract thinking, many people were shocked to learn that machines can think like humans.

1 ) What is machine learning?

Machine learning is a subfield of artificial intelligence able to learn and adapt without following explicit instructions by using algorithms. In simple words, defined as the capability of a machine to imitate intelligent human behavior. For example; if you train a model to recognize a field, an image… it can’t learn a task outside his field of knowledge on his own.

2 ) What is the difference between machine learning and artificial intelligence?

Artificial intelligence is the simulation of human intelligence processes. It matters on how this machine applies this knowledge using deducible logic. Machine learning is a subset of artificial intelligence that allows machines to learn on their own using data without being specially programmed for it.

3 ) Who uses Machine learning and for what reason?

Machine learning uses a variety of algorithms to make decisions, predict results, cluster results and detect anomalies. Anomaly detection identifies data that is different from the data identified in a given cluster. Example; A machine learning model will analyze images of cars and motorcycles and create two clusters – one for cars and one for motorcycles. If the model analyzes the image of a bird, it detects that this image is an anomaly. There are many uses of machine learning in all industries including financial services, insurance, healthcare, retail, government, military, agriculture.

4 ) Examples and applications of machine Learning

Search engines use machine learning to make suggestions when you are looking for specific information or a specific site. Insurance organizations use machine learning technology to identify claims fraud and to predict bonus and penalty amounts for their policies. Automakers use machine learning for image recognition in cars and trucks. Netflix also uses machine learning to recommend what you might want to watch next.