In the past decades, we have gathered lots and lots of data and the advancement in the computation power and algorithm, which helps us in making the optimal Machine Learning models.
Machine learning is on hype now a days. Most of the people who are not aware about the Machine learning jargon, are confused about what it really is.
Today, we will burst the most popular myths about the Machine learning. Like – Some of us think that Machine learning will take all the major jobs and might robots will rule our world.
You will also came to know about the complete path of learning the machine learning and how to earn from your machine learning skills. So, lets get started with What really Machine learning is.
Machine learning is one of the most popular application of Data Science. It is the branch of artificial intelligence which deals with the vast amount of data and designing of optimal algorithm which makes machine able to think and can take decision by itself, without any human interruption.Also Read: DuckDuckGo vs Google: 12 Cool Things You Can Only Do In DuckDuckGo
As the name suggest “Machine learning”, it is the practice of making machine able to learn and think by itself from the experiences(negative or positive).
How to learn Machine learning
Like other technologies, the course of machine learning is much definite. But unlike other technology it is much more disciplinary field.
You have to put the regular efforts for becoming a machine learning engineer. It may take you 3 – 12 month for getting comfortable with machine learning and building your first machine learning project.
So, I will share with an easy to follow strategy or steps, which you can follow to learn machine learning.
- Choose the Programming Language – Basically, you can choose any programming language for machine learning. But the one which I will suggest you is Python. Because it is easy to code in python as compared to other language. Python is the only language which is rich with number of Machine Learning Libraries.
- Learn Mathematics – Now, make sure that you don’t have to be genius in mathematics. Basic knowledge of some topics of mathematics is enough and those topics are Linear algebra, Probability, Statistics and Calculas. If you have the basic knowledge about these topics, you are good to go.
- Machine Learning Concepts – Make yourself comfortable with the jargon of machine learning. There are many concepts and term in machine learning which our must know. Like – modelling, training, EDA(Exploratory Data Analysis), Machine, various regression and much more. For this, you follow any regular article or your favourite youtuber or instagrammer.
- Machine Learning Algorithms – After you know the working of machine learning and it’s concepts. You can move to algorithmic part. There are many Machine Learning Algorithms. Like – Linear Regression, Logistic Regression, Decision Trees, Artificial Neural Networks and many more. You should get your hand dirty with these machine learning algorithms as these very important for you to understand.
- Machine Learning Framework – Machine Learning Framework are the set of tools and libraries, which makes your life much much more easy as a machine learning engineer. These framework makes machine learning so easy that even none mathematical background person can also work on it. Some of the best framework for machine learning are TensorFlow, Scikit Learn, PyTorch , Amazon Machine Learning and more. So, you should definitely learn these frameworks.
- Make Projects and participate in competitions – Now that you have good knowledge of Machine Learning. You are ready to make your projects for portfolio. This will helps you a lot in brushing up your machine learning knowledge and boost your professional life as well. You should also participate in competitions and hackathon, which will give you a different perspective as you will collaborate with other machine learning enthusiasts.
How Machine Learning works
Machine learning completely works on the data. Without data, Machine learning is not possible. That the reason why the big companies like – Google and Facebook are working on advancement of Machine learning because of abundance of data they have.
In Machine learning, we focus on designing the algorithms which takes huge amount of data and train the machine with that data. After the machine gets trained, it is ready to build the model.
Model in Machine learning is the way by which a specific problem is solved in different conditions.
There are various pre-build models available with Machine Learning Framework like – Scitik Learn, TensorFlow, PyTorch, Amazon Machine Learning and many more. They provides us the number of pre-build Machine Learning Model which makes our work much easier, eliminating all the tedious work for us like – Algorithm designing, Training the machine and much more.
This also mean that knowledge of mathematics is not mandatory for becoming Machine Learning Engineer. But we know that there is no fun in working the technology which we can’t understand.Also Read: What is DevOps
So, the conditions will be more favorable for us, if we know the mathematics behind the Machine Learning algorithm we are using.
Top 10 Application of Machine Learning
As we know that Machine learning is a high in demand job because of its vast applications in different Industries and fields. So, let talk about some of the Applications of Artificial Intelligence and Machine Learning in Industries.
- Chat bots
- Stock Market Prediction
- Virtual Personal Assistance
- Search Engine Result Refining
- Self Driving
- Online Fraud Detection
- Traffic Prediction
- Medical Technology
- Email spam filtering
So, these are the foot steps which I follow and you should to for your Machine Learning journey. Hope you like it. If you have any suggestion. Let us know in the comment section below.