Random Forest Algorithm

Random Forest Algorithm is an integral part of machine learning, data science, and Artificial Intelligence.  Random forest algorithm is a classification method of observations by the formation of decision trees. The importance of categorization and classification of observations is precious to any business. 

Predictions based on the Random Forest Algorithm as a part of data science have impacted a plethora of industries like transportation, healthcare, travel, sports, the Government, and economies of the world, social life of people in the world, the e-commerce industry. There is immense scope for candidates in the industry above after studying the Random Forest Algorithm on a standalone basis or as a part of the broader curriculum of Machine Learning, Data Science, and Artificial Intelligence. 

What is Random Forest Algorithm

Within the healthcare industry, the Random Forest Algorithm is used to categorize data collected and used for drug sensitivity analysis in patients. Random Forest Algorithm can help data scientists in creating complex combinations of chemicals that can be used to create specific medicines and a line of treatment depending upon the medical history of the patient.

Within the banking sector, Forest Algorithm is used for the detection of frauds. Banks have a large base of loyal customers who use banking for different purposes. However, some of them are fraud customers, and with the help of the Forest Algorithm, fraudulent transactions can be identified by analyzing the pattern they form.

Random Forest Algorithm and conclusions made by it are widely used by financial analysts to predict stock market movements from both a bottom-up and top-down approach. They also contribute to the risk management sector by categorizing the risk factors and predicting outcomes that minimize losses.

Random forest Algorithm as a part of Machine learning and Data science has helped in the recent boom of the startup world. The Algorithm creates pattern trees based on data on consumer buying behavior. Random Forest Algorithm categorizes data is such a manner that e-commerce players can predict the next buy or need of the consumer and present a tailor-made product or solution to them as an option in advance.

Candidates certified with Random Forest Algorithm find employment in the Government. The Government has a vast database of information about the people of its country. It needs such algorithms to formulate and implement policies effectively for the betterment of the country. Besides this, criminal activities like tax evasion and border security can be enhanced by identifying the categories of sensitive groups within the population using the Forest Algorithm.

Random Forest Algorithm has always helped the sporting industry from how to play, how to win, and how to pick teams.

Random Forest Algorithm in Machine Learning

Courses in the Random Forest Algorithm as a part of Data Science/Analytics and Machine learning is available in both online and offline formats. It is generally regarded as either a post-graduation degree or certification with a prerequisite of a Bachelor’s degree in science/engineering/mathematics/statistics/commerce.

In India, the institutes which offer courses of which  Random Forest Algorithm is a part, are Great Learning, upGrad, Talentsprint, Jigsaw Academy, Analytix Labs, Simplilearn, Amity Online, Edureka, Applied AI course, Pearson Professional, IIIT Hyderabad.

Courses in the Random Forest Algorithm as a part of Data Science/Analytics and Machine learning have a duration, which is anywhere between 6 months to 2 years, depending upon the type of course. The total fees range from 30,000 INR to 3,00,000 INR depending upon the model, the type of degree awarded, the placement record of an institute, and the duration of the course.

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About the Author

Rachit believes in the power of education and has studied from the top institutes of IIIT Allahabad, IIM Calcutta, and Francois Rabelias in France. He has worked as Software Developer with Microsoft and Adobe. Post his MBA, he worked with the world’s # 1 consulting firm, The Boston Consulting Group across multiple geographies US, South-East Asia and Europe.

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