For pursuing a career in machine learning and artificial intelligence, a little knowledge of coding is necessary. Programmers having knowledge of coding are able to implement codes more efficiently and they are also able to work on algorithms as per the requirement by different businesses.
Ironically, individuals interested in pursuing a career in this field, begin from concepts like supervised, unsupervised learning, neural networks and reinforcement learning instead of coding and learning to write a code. It is mandatory to understand the basic concepts like coding first before the other core topics which are required in machine learning.
Programming languages for machine learning
A Machine Learning Engineer aspiring to make a career in machine learning or planning to upscale to data analytics or data science should be master at the below programming languages:
Python Programming Language
Without any doubt, Python has emerged as one of the most important programming language for machine learning due to its flexibility, and readable code. The Python libraries and packages are really helpful in saving time and reducing effort when it comes to complex machine learning application and frameworks. TensorFlow or Keras is an effective tool for deep learning; Numpy can prove to be good tool for textual data and scikit-learn is excellent for implementing ML algorithms.
R Programming Language
Data Scientists working with large quantity of data find R Programming language quite helpful in statistical computing. R programming language can be used for different machine learning applications like data visualization, data sampling and supervised, unsupervised learning. R is also used for implementing machine learning methodologies such as classification, regression and decision tree formation.
Java Programming Language
Machine learning engineers with Java background don’t need to learn Python or R. It is possible to develop web apps, mobile apps and games with Java.You can start with any language of your choice, be it Python, R or Java and make a fruitful career in machine learning.
Does Machine Learning require Maths?
As machine learning is based on mathematical calculations, it is important for you to understand why maths used and why is it important to be thorough with mathematical concepts? For creating algorithms which can help in using data and making predictions maths is required. Mathematics is extremely crucial for solving Data Science projects and defines underlying concepts behind algorithms. Machine learning is mainly structured on four important mathematical concepts:
- Linear Algebra
- Statistics
- Calculus
- Probability
Whatever be your goal, whether you want to become a data analyst, data scientist or a Machine Learning Engineer your primary focus of study should always be Mathematics. From analyzing company transactions or for understanding the daily working of day-to-day market, Maths is used in every business. Maths is used in many Industries like IT, Manufacturing and Retail to study sales, production, for paying wages or even for goods intake.
Although there are plenty of ways available to explain important mathematical concepts but you must look up for a book which talks about all the concepts in detail and practice them for understanding.
