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Home » 6 Prerequisites for starting learning Machine Learning
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6 Prerequisites for starting learning Machine Learning

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6 Prerequisites for starting learning Machine Learning
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Machine learning refers to the ability of machines to perform complex tasks without being explicitly programmed to do so. It is a multidisciplinary domain at the intersection of subjects like computer science, algebra, statistics, calculus, etc.

Machine learning encompasses various techniques and consists of a wide variety of tools for specific purposes, including regression, classification, deep learning, random forests, neural networks, supervised learning, unsupervised learning, and reinforcement learning.

Machine learning is used in many areas of everyday life, such as on Facebook, Instagram, Quora, Reddit, Amazon, and Flipkart. Search engines rely heavily upon machine learning to bring credible and useful search results, while navigation services use it to provide reliable traffic predictions.

Weather forecasts are fast abandoning large and cumbersome models from meteorological science and replacing them with machine learning-based approaches. Language translators, text-to-speech engines, computer vision, and self-driving cars all rely upon machine learning.

The rapid development of machine learning has taken the job market by storm, with many opportunities opening up across tech companies, banking and financial services organizations, new-age startups, and legacy giants alike.

However, one needs to meet various criteria to learn machine learning satisfactorily. These include having a strong grasp of high-school algebra and linear algebra, elementary trigonometry, probability, statistics, Calculus, and a programming language, with Python being the most popular choice.

Pickl.ai is the educational vertical of TransOrg Analytics, which is a leader in working out Big Data and Machine Learning solutions for transforming businesses.

Pickl’s goal is to democratize education in data science and machine learning for all. They provide curated courses for high-schoolers, collegegoers, graduates, and working professionals, supplemented with interactive assignments, live classes, and project formulation.

Placement assistance is also provided in the form of mock interviews and resume-building sessions, and the instructors are seasoned data veterans with decades of experience in grappling with the challenges of the fast-changing domain.

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