Information about skills
There are so many necessary skills and education needed for a tough field of Machine learning engineering heavily involving , Statistical Analysis and Probability, data structures, programming algorithms, and mathematics. We will talk about each of those categories and why they are important>
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Analysis and Probability
Having an understanding of statistical concepts, including probability, distributions, and hypothesis testing. With this, you can design accurate models, make informed predictions, and uncover patterns within complex datasets, enabling data-driven decision-making and practical applications of machine learning techniques.
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Programming
Programming is a set of instructions for the computer to follow, through coding. You can write algorithms, clean and organize data, build and train models, and test their accuracy. Most often, ML uses these languages:
- Python
- Java
- R
- Scala
- C/C++
Since there is a lot of coding involved, you will be typing a lot! Typing away.
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Math
Math is really important! Having the right formulas provides sets of instructions that allow computers to learn from data, make predictions, and improve performance. There are many types of math required for ML, but here are a few key ones:
- Linear Algebra
- Calculus
- Probability Distributions and Statistics
- Geometry
