Data Science VS Machine Learning
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You have listen the words like Data Science and Machine learning. And did you think about the Differences Between Machine learning and Data Science. If we consider this Two words. This two words will have different meaning exchanged very often. In this blog we are going to discuss Data science online training. And it also explains concepts of Deep learning and how this are connected to Big Data. In the first place it explains Data Science VS Machine Learning.Data Science VS Machine Learning

Data Science VS Machine Learning:-

In general when we find an Answer to a Question in  traditional way. We provide definition in point to point way approach for finding the solution. If we take an Instance, for building a self-Driving Car. We have to Define some points like the road doesn’t have any traffic and car speed Calculations. Vehicle is Front, left or right and it do actions according to the situations. So the whole Process works under if-else statements. In machine learning this we don’t provide, this method of statements to solve the problems.

For this process in machine learning, we will provide Inputs and outputs and our algorithm learns. By that we can Develop the solution for the problem itself, that is where the beautiful thing happens. Some cases for every critical problem, it may seen that we don’t understand, what is the thing , that our sample has Designed to solve the question. We will consider that  it is in working Condition. We will discuss this about when we deal with Deep learning and Big Data. As a matter of fact this  the part of Data Science VS Machine Learning.

Machine learning is of three Types :-

1)Reinforcement Learning :-

In this Method of learning, Review is not there at each step model. Rather than model get Review only when it gets a pointed Target. If we take example of chess game if you win the game it gives Review and If it wons the game it has considered as supervised Algorithm. And we will provide Review for every movement. Correspondingly Data Science VS Machine Learning is Included in Reinforcement Learning.

2)Supervised learning :-

In this our data is managed and Every Input is having well defined output. We can take a example so that we can understand Easily. so, We are assigning Pictures of animals to our model. And we have to assign that pictures with that corresponding animal. if we have assigned picture of Dog to our Model. Then we will get the output of the Dog. In the simple method we are expecting Model is self-learning.

3)Unsupervised learning :-

In this we feed unlabeled Data to our Model. For Instance if we take professor and students. If a professor want to Differentiate all the students. Into Groups Based on Different types. Like Average study hours,percentages,how many subjects, they have studied and their Hobbies. If you provide this Data to the unsupervised Model , this do you work by, dividing Groups of students according to their Interests. Unsupervised learning is used by sellers to Differentiate their customers according to their interests. Comparatively it is the part of Data Science VS Machine Learning.

Now  let us have a look over Data science.

Data science is Came From Two words such as Data and Science. Data is unprocessed set of things. This things should be Processed. If we consider an Example Image is Data. This blog is Data. On the other side. Information is what we mean , when we preferring to Data and we get Information, when Data is presented and Processed in a beautiful way. So it can be called as Information Science. In Data Science we considering Science also . So for proposing it as science, we need to consider scientific method and science now.

Data Science is practical method. It is having science basics. And Data science has this type of  topics.

1)Machine Learning :- As Mentioned Above

2) Science of Computer :-you have to know Command-line, vectors operations.

3) In mathematics you have to know, Basics of mathematics and Calculus and probability. Additionally all the above concepts will explain Data Science VS Machine Learning.

Recommended Audience :

Software developers

Database Administrators

Team leaders

System Admins


There is nothing much prerequisites to pursue the course. So, It’s good to have a basic knowledge of Data science algorithms and basic knowledge of programming languages like python for the purpose of automation. But not mandatory. finally, Trainers of OnlineITGuru will  teach you all the basics required for Machine learning Online Course

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