Machine Learning is an application of artificial intelligence where a computer/machine learns from past experiences (input data) and makes future predictions. This allows the machine learning models to make assumptions, test them and learn autonomously, without being explicitly programmed. It is accomplished by feeding the model with data and information in the form of observations and real-world interactions. There is a vast number of industries and applications that utilize machine learning to make themselves more efficient and intelligent.
Machine Learning came into existence in 1946 when Polish scientist Stanislaw Ulam, got frustrated while trying to figure out the probability of winning a game of solitaire. Then it was in 1959 that computer scientist, Arthur Samuel coined the term “Machine Learning”. He described it as a “Field of study that gives computers the capability to learn without being explicitly programmed”.
According to Payscale, the average salary for a Machine Learning Engineer is $111,297. As the companies race for digital disruption, the demand for machine learning as a skill has also grown exponentially in the past couple of years. So it is time to add another skill in the resume as machine learning is set to transform our future. Or maybe you can be learning machine learning if you want to build your own J.A.R.V.I.S. Or are simply getting bored in COVID-19 lockdown and want to learn something that can help your career.
One can start with learning pre-requisites like linear algebra, multivariable calculus in mathematics and Bayesian probability in statistics.
This Machine Learning online course is curated and developed by SMEs from top product-based companies to meet the needs of the current data-driven industry. It covers a detailed overview of various algorithms and techniques, such as regression, classification, time series modeling, supervised and unsupervised learning, Natural Language Processing, etc. You will also use Python programming language to write code for implementing numerous algorithms in this certification training.
After learning Python, the next thing one must learn how to work with and manipulate data. This is done by familiarizing with OpenCV, pandas, NumPy and Matplotlib. OpenCV is helpful analyzing images/videos and applying Cascade’s and more. pandas will help in working with data frames and structured data, these are tables of information like Excel file. NumPy will help to perform mathematical operations on data and mine patterns. Lastly Matplotlib helps in plotting mathematically operations visually in dimensions.
- As part of this ML program, you will work on real-world projects in the fields of e-commerce, automation, marketing, sales, banking, Internet, insurance, and more.
- Our projects include building a chatbot to answers customer queries, building a recommendation system, fare prediction for taxi booking, analyzing the trends of COVID-19 with Python, customer churn classifier, etc.
- Upon the successful project completion, your skills will be equivalent to 6 months of comprehensive industry experience.