While differentiating between the two things, it’s very important to get proper knowledge of both the subjects. It is not like you will just make assumptions like Machine learning is superior to statistics or vice versa. You need to have a proper understanding of all the facts and figures and why there is a need for studying them separately. Most people find it quite difficult to understand the main difference between Statistics vs Machine Learning. Although both of them are branches of the same field, there are certain things that make them quite different from each other.
Machine learning and Statistics are interrelated to each other. While Machine learning is a subset of Artificial intelligence and is used in a number of fields like fraud detection, real-time ads, web pages, text-based analysis, network detection, image recognition, spam filtering, etc. On the other hand, statistics is the process of collecting, analyzing, interpreting, and organizing data. When statistics is applied to scientific or industrial problems it gives rise to the Statistical modeling process.
This was an overview of Statistics and Machine Language. Now, we are going to discuss in detail both of them, their benefits, and what are the main differences between Statistics vs Machine Learning.
- Machine Learning: As the name suggests “Machine”, it’s a process where you let the machine train upon itself and produce the desired results. It deals with creating different kinds of algorithms that learn directly from available data without being dependent on rules-based programming. Machine Learning was originally a part of Artificial Intelligence that dealt with different aspects to study human behavior but later it became a separate branch that now deals with creating algorithms, learning data, and accomplishing tasks without any set of instructions required. Machine learning plays a very vital role in the growing field of Data Science. Using different kinds of algorithms and operations, Machine Learning has an essential part of many leading organizations such as Facebook, Instagram, Uber, Google, etc.
Uses of Machine Learning
- Image Recognition
- Online Fraud Detection
- Traffic Prediction
- Search Engine Result Refining
- Social Media Services
- Statistics: In simpler words, we can say statistics is the branch of mathematics where data patterns are driven using various mathematical solutions. Statistical learning stresses more on processing raw data into desirable information which forms the basis of machine learning algorithms. Although there is a big difference between Statistics vs Machine learning, you cannot ignore the fact that somehow they are interrelated to each other. Machine learning is all about predictions, supervised, unsupervised learning while the study of statistics includes sampling, population, hypothesis, etc. If we define statistical modeling, it is a close relationship between different mathematical equations.
Uses of Statistics
- Statistics is used in research and analysis of different fields
- Weather Forecast
- Quality Testing
- Financial Market
- Business Statistics
Main Differences between Statistics Vs Machine Learning
- Machine learning is a well-prepared set of rules and regulations provided by the user where the machine understands and interprets the information by itself. On the other hand, statistics is complete mathematics based on the concept of finding different patterns from the data.
- Machine Learning is the subset of Artificial intelligence and computer science while statistics is completely based on mathematics. Or you can say the statistical model is a subfield of mathematics
- Machine Learning is a modern technology that has gained a boom in past few years. While statistics existed long before even when computers were invented.
- For machine learning, you dont need any prior data or facts. You just need to provide the information and algorithms automatically process it and provides you the results. While in statistics learning, you need to collect the data from various sources, study. And interpret the information and then come up with the predictive results.
- Machine Learning helps us to quickly produce the models that are used for analyzing data and deliver faster solutions. On the other hand, statistical applications are applied to low dimensional data sets. But it has a number of applications in all types of areas.
- On the other hand, statistics have different types: Forecasting continuous variables, Regression, Classification, etc.
- Machine Learning is mostly used in the fields of Data Analysis and Artificial Intelligence while statistics are used in various fields of mathematics, Artificial intelligence, data science research labs, etc.
- Machine learning provides input and output in the form of features. And variables while statistics learning provides input and output in the form of data points.
In a nutshell, we can say that Statistics vs Machine Learning are somehow associated with each other. Both are the same branches of predictive modeling that are coupled in such a way that one leads to another. Each of them has its own importance and uses. And both of them should be analyzed and studied in a better way.
These were some of the main points and differences between Statistics vs Machine Learning. I hope this article was helpful. And it might have cleared your doubts regarding various aspects of Statistics and Machine Learning.