Sunday 17 July 2022

Find your Life, Find your Passion and Find your Life - IKIGAI

No comments : Posted by Millioninformations at 01:08 Labels:


 

Watch my video on Youtube:


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What is Data Science? - End to End project - part 1

No comments : Posted by Millioninformations at 01:02 Labels: ,

 


In this post, we will see how a simple data science project life cycle will be!

Data Science Project Life Cycle

1. Understanding the Business Problem


Without a business requires no project exists. So once the client approached us for a solution. Then we have to understand their business problem and requirements. We have to get clarification of all of your questions and queries initial stage of the project to avoid back and forth.

The client will approach a data science firm which will be mostly a Marketing Research firm or Data Analysis firm.

They will have a kick-off call meeting where they will discuss the business problem statement and their requirements with the technical team and frame the steps to be executed.

After the meeting they will identify the below:

1. Exact Problem statement
2. Where and how to collect data from
3. Budget and Duration of the Project 
4. Required Output files
 

2. Data Collection

Once the problem statement is identified and the data collection process is defined then the project goes live.

Data Collection:

There are various ways to collect data.

1. Survey
2. Telephonic Interview data
3. Data collected from real-time places such as hospitals, clinics, and individual persons.


The data will be collected based on the requirements of the client, they most probably define a questionnaire to collect the data.

Once the data is ready the project will start in terms of technical part.

3. Data Analysis

Data analysis is the major part of a Data Science project. It is also the crucial part of the entire project where all the other projects depend on the data provided by the data analysis team. So it is really very important to work more cautiously when doing the data analysis.

There are different tools to do the data analysis which we will discuss in the upcoming episodes.

During the data analysis process, the team will prepare a cleaned version of data after checking the data quality, genuine form of data and more focus on the valid data.

The team will also build some partial insights with visualization for the client to look at to know that the project is on right track. Also the client can direct the team to focus on a few areas based on the analysis they did so far.

4. Machine Learning Model

Most of the projects can be 90% completed once the Data analysis project is over. Only a few projects need a machine learning model based on the complexity of the data and volume of the data. 

The Machine Learning models will be helpful to automate our work and make the big volume of data analysis in a simple and faster manner. We will learn more about machine learning in upcoming episodes.

5. Insights

Finally, we will get prepared with the insights and output files in the format the client has requested. It can be a simple excel, CSV file, text file, pdf, charts, graphs, slides etc...

There will be a secured mode of communication to deliver the projects.

Based on the client's suggestion there might be some more tune-up in the insights else the project can be sign-off.

Hope this article might be helped you in understanding what a data science project will be like. In upcoming episodes, I will share the tools and technical part of data science. 


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Saturday 16 July 2022

What is Data Science?

3 comments : Posted by Millioninformations at 22:47 Labels: ,


 


Data Science is a combination of multiple disciplines that use statistics, data analysis and machine learning to analyze data and extract knowledge and insights from it.

What is the Use of Data Science?




 Data Science is the art of providing insights based on the provided data from the client or data collected based on the business requirement.

Data Science is a field that has gained significant attention in recent years, thanks to the increasing importance of data-driven decision making. In simple terms, Data Science is the process of extracting insights and knowledge from large and complex data sets.

The field of Data Science is interdisciplinary and draws on concepts from computer science, statistics, mathematics, and other related fields. It involves a combination of data collection, cleaning, processing, analysis, and visualization, with the ultimate goal of extracting meaningful insights that can be used to inform business decisions.

One of the key benefits of Data Science is that it allows organizations to gain a deeper understanding of their customers, operations, and overall performance. By analyzing data, businesses can identify trends, patterns, and areas for improvement, which can ultimately lead to increased efficiency, profitability, and customer satisfaction.

Data Science is also a rapidly growing field, with high demand for skilled professionals who can work with large and complex data sets. In fact, according to the U.S. Bureau of Labor Statistics, employment of computer and information research scientists (which includes Data Scientists) is projected to grow 19 percent from 2020 to 2030, much faster than the average for all occupations.

If you're interested in pursuing a career in Data Science, there are a variety of educational and training programs available, ranging from online courses to degree programs. Many of these programs focus on developing skills in areas such as data analysis, machine learning, and programming.

In conclusion, Data Science is an exciting and rapidly growing field that offers numerous opportunities for skilled professionals. By leveraging the power of data, businesses can gain valuable insights that can help them make better decisions and achieve greater success. If you're interested in pursuing a career in Data Science, there are a variety of resources available to help you get started.

That Insight will be the output of a data science project where it will help us to make any of the below.

1. Decision Making

2. Prediction

3. Pattern recognition

these things will help us to make better decisions on business plans, products to be launched, prioritising the priority work, and strategies that will make more revenues.

This is why companies invest a lot in data science.

In the upcoming post, we will learn about How an End to End data science project will be, and what are the opportunities in this domain.



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Thursday 17 February 2022

Python practice programs for beginners - Day 20

2 comments : Posted by Millioninformations at 01:49 Labels:

 


Day 19 Solution:

adding items to list in python


Output:


Practice the same kind of programs and if you practice any new program kindly mention in it in comments.

Also read: How to install Android Studio


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Python practice programs for beginners - Day 19

1 comment : Posted by Millioninformations at 01:37 Labels:

 

Python practice programs for beginners - millioninformations

Day 18: Solution




Day 19: Getting list items from users at run time and printing it.



You can practice the above program.

Day 19 Task: Get the Hollywood movie list going to get released in 2022 Summer from the user and print it.




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Python practice programs for beginners - Day 18

1 comment : Posted by Millioninformations at 01:13 Labels:

Python practice programs for beginners - millioninformations

 Day 17 Solution:



Day 18: Introduction to List

A list is a collection of items. The items can be of any type.

Example: [1,2,3,5.5,"a",True]

How to print a list in Python?

Output: 

[1, 2, 3, 4, 5.5, True]


But if we want to print the list items alone we need to use for loop.



Output:

1

2

3

4

5.5

True


Day 18 Task: Create a list for latest gadgets and display it.





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Monday 14 February 2022

Python practice programs for beginners - Day 17

1 comment : Posted by Millioninformations at 01:07 Labels:

 

Python practice programs for beginners - 17

Day 16: Solution

Python Multiplication table program

Output:

Python Multiplication table program


Day 17: While loop

Syntax:

while condition to check:

    statement to be executed

Example: 

   



Day 17 Task: 

Get a number from the user and print the odd numbers in that range.





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Saturday 12 February 2022

Python practice programs for beginners - Day 16

1 comment : Posted by Millioninformations at 20:30 Labels:

 

Python practice programs for beginners - Millioninformations

Day 15 Solution:


Output:

for loop even number


Day 16: For Loop

Mini Project 2:

Get a number from the user and display the multiplication table of that number. You can also get them up to which number you can display the table.



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Friday 11 February 2022

Python practice programs for beginners - Day 15

1 comment : Posted by Millioninformations at 18:30 Labels: ,

 

Python practice programs for beginners - Day 15


Day 14 Solution:


Output:

Day 15 : for loop

If you see in the above picture the output is starting from 0 and ending with 9. If we want to start from 1 to 10 then we need to change the code in the range.


In this we have to use from 1 to 11 (10+1) because the loop runs from 1 to whatever the value mentioned at end position -1.

Output:

Day 15 Task: 

Get start value and end value from the user at run time and print all the even numbers between that range.


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Thursday 10 February 2022

Python practice programs for beginners - Day 14

1 comment : Posted by Millioninformations at 21:00 Labels:

 

Python practice programs for beginners - Day 14


Day 13 Solution:

Python Grade Checker Project Source Code:

Download Source code


Day 14: for loop

Syntax: 

for val in sequence:

    statements to be expected in the loop

val - variables

sequence - may be a range or list of items

Example:

Output:


Task: Print your name 10 times






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