We are living in the era of automation, most of the tasks we do in our daily routine are automated. Machine learning plays a major role in automating things. It is one of the top technologies at present and has a great future. It is a branch of Artificial Intelligence that builds algorithms to find hidden relations and patterns in data. In this article, we’ll discover about Machine learning and see how it is used in the real world. Let’s begin this text with a famous quote on Machine learning.
“Machine learning is that the last invention that humanity will ever get to make.” ~Nick Bostrom
What is Machine Learning?
Machine Learning is a set of algorithms/techniques, which naturally learns through data and improves over time as they’re exposed to more data. Algorithms and data are the key part of machine learning actions. Algorithms are constantly under work to become more accurate and reliable but the main factor that determines the success of the Machine Learning model is the data available for training the same model.
The workflow of the Machine learning model is described below.
Types of Machine Learning
There are three types of machine learning and they are as follows
1. Supervised Learning
2. Unsupervised Learning
3. Reinforcement Learning
Supervised Learning
Supervised learning means training the model with labeled data i.e., data with both input and
output labels.
Unsupervised Learning
In the case of unsupervised learning, the model is trained using unlabelled data i.e., In this
case, we don’t know the output for a specific input value.
Reinforcement Learning
Reinforcement learning makes the machine learn from the result of its actions i.e, the model
will learn whether to perform a specific operation or not by its experience.
Programming Languages for Machine Learning
Below is a list of the most popular programming languages for Machine learning.
Python is the most famous Machine learning language and the reason is Python is easy to use and has a wide number of Machine learning packages. It is used by almost 60% of Machine learning developers.
R
R is the most popular Machine learning language among statisticians as it offers an excellent environment for data analysis, manipulation and visualization. It is a highly flexible and compatible language.
Java
Java is not famous like Python and R for Machine learning. But it is gaining high popularity as the developers who use Java don’t need to learn Python or R to move to the Machine learning field. And the other big reason is that most of the open-source big data tools like Hadoop, Spark are written in Java.
Golang
Golang is a programming language that was developed by Google and was launched in 2009. It is also a good choice for Machine learning especially when we have to deal with large datasets because in Golang the code compiles to binary form that makes it fast. It is easy to use and has a good amount of Machine learning packages.
LISP
LISP is the oldest programming language used for Artificial Intelligence. It is the reason for the development of Artificial Intelligence. It is considered the most powerful language for solving complex problems and it has many Machine learning languages like Python, R, Java and many other.
Machine Learning Applications
At present Machine learning has its applications in almost every domain. Below are some of the top applications of Machine learning.
Virtual Assistants
Weather Forecasting
Stock, Crypto Price Prediction
Social Media Services
Anomaly Detection
Video Surveillance
Recommendation Systems
Sentiment Analysis
These are very few of the countless applications of Machine learning.
Summary
In this article, we learned about Machine learning, its types, programming languages for Machine learning and its applications. This is just an introductory article on Machine learning, we tried to cover most of the common things about Machine learning which one should know before starting their Machine learning journey.
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