Hi my name is Malhar today I came with super knowledge of regarding Data Science and Python. as a result, I will give brief explanation regarding what is data science. Python for data science.
You all know that data science is a very fastest growing field in the world. Because you know that everything will become an automatic. Means Computer will take decision instead of human. For this First we have to train the computer in such a way that it can take proper action which is not harmful to others. Let’s first we will see what is Data science and It’s Introduction.
What is Data Science?
First we will see Definition of Data Science so “Data science is transforming data into meaningful insight for making decision, Competitive analysis and offering new opportunities.”
Basically Data is a virtual gold in the language of information technology. And this data is basically raw data but raw data is not very useful so it must be converted into meaningful insight so this data science by it we can do easily.
If we take one example of ecommerce data then which products perform better selling out of thousands of products this can be conclude via only data science.
Why Data science is so important?
You can see day by day internet uses and content creation is increase and increase. If we see as per latest analysis then in last two year there is approx. 90 Percent in the world.
There is approx. 400 million tweets generated per day.
There is approx. 3 billion likes of Facebook generated every day.
There is multiple Data Sources like Facebook, Twitter, LinkedIn, Blog, comments, site contents, etc…
As per one sentence the data is doubled all over the world in 2 year. And this timing is decrease day by day due to increase in internet uses.
Flow of Data science process
What makes Data Science Different?
Data analytics supports and encourages changes between hypothesis-based and pattern-based reasoning.
There are 6 main changes done in Data Science.
- Crucial change from customary insightful methodologies.
- Intends to frame or refine theories and find new scientific ways.
- Tradecraft and the interaction among inductive and deductive thinking by giving huge bits of knowledge.
- Models of reality at this point don’t should be static and observationally based.
- Continually tried, refreshed and improved.
Data Science
There is basically three main part in Data Science.
- Statistics
- Data Visualization
- Machine Learning
Information sciences is an umbrella idea that incorporates all the regions that can offer capacity to gigantic volumes of information.
Statistical investigation, But likewise progressed AI where in the PC obtains information to anticipate patters utilizing pre constructed calculations, perform different activities on the information to decipher designs. Representation to address the information in effectively decipherable arrangement.
Now we will understand this main three part one by one.
What is statistics?
Statistics is a Part of Mathematics. However main use of statistic in Data analytics is to transform or convert Data into meaningful information which is useful for decision makers.
There are two types of Statistics used in Data Science?
- Descriptive Statistics
Descriptive statistics means to organizing and summarizing data for decision makers. For Example Tables, Graphs generally used to organize data such as average data to summarize data.
Descriptive value from population is called statistics.
2. Inferential Statistics
Inferential Statistics means it is a sample from entire population and to make general conclusion for whole population. When we take small sample from entire population then it may be not perfect and will provide limited information for whole population.
What is Data Visualization?
When we collect data from population as we have discussed and when we present data in graphical, Map or pictorial form for better understanding it is known as Data Visualization.
Measure benefits of Data Visualization is it provide better understanding about data. as a result, It shows better relationship between different parameters. You can direct interact with data.
Types of Data visualization
- Charts
- Maps
- Flow
- Matrix
- Info graphic
- Network
- Time series
- Hierarchy
What is Machine Learning?
Machine Learning is the main future of Data analytics. But it is totally dependent on Prediction value as per the current and past data study.
In Machine Learning There is multiple Algorithm and Techniques. As a result, in Machine learning algorithm studies how to automatically learn and make a future prediction depending on current and past observation.
Machine learning will program the machine means computers to optimize performance and prediction as per observation.
Machine Learning can do when Human Expertise ends and human cannot explain their expertise.
There are multiple application of Machine learning is there for example Finance, manufacturing, bio informatics, web mining, medicine, telecommunication retail market.
There are basically three type of algorithm available in Machine Learning
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
This is all about what is data science. For these all three type I will write individual article because each part is very big for understanding so soon I will write for each in detail.
Data Analytics is very big thing for future.However there is best language used world wide is python for data analytics it is easy to learn and understand .
I thing you heard about Machine learning and Artificial Intelligence so this is the future of world.
I hope you got enough information regarding what is data science. as a result, Thanks for reading
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