Piyal Banik Profile picture
Jun 16, 2021 9 tweets 3 min read Read on X
There are 8 built in classes (variable types) in Python. A thread🧵👇

#Python #100DaysOfCode #CodeNewbie
1. Boolean- The Boolean data type is a truth value, either True​ ​ or Fals​e. Image
2, 3. Integer and Float - An integer is a positive or negative number without floating point. A float is a
positive or negative number with floating point
precision. Image
4. List - A container data type that stores a
sequence of elements. Image
5. Tuple - Tuples are used to store multiple items in a single variable. Image
6. String - Python Strings are sequences of characters. Image
7. Set - A set is an unordered collection of
elements. Each can exist only once. Image
8. Dictionary - The dictionary is a useful data structure for storing (key, value) pairs. Image
That's it for the thread 🧵👋

Follow @PiyalBanik for more threads like this.

Feel free to DM ✉️

• • •

Missing some Tweet in this thread? You can try to force a refresh
 

Keep Current with Piyal Banik

Piyal Banik Profile picture

Stay in touch and get notified when new unrolls are available from this author!

Read all threads

This Thread may be Removed Anytime!

PDF

Twitter may remove this content at anytime! Save it as PDF for later use!

Try unrolling a thread yourself!

how to unroll video
  1. Follow @ThreadReaderApp to mention us!

  2. From a Twitter thread mention us with a keyword "unroll"
@threadreaderapp unroll

Practice here first or read more on our help page!

More from @PiyalBanik

Aug 17, 2021
#DataScience Project 4

Customer Segmentation

- Use Machine Learning to create a model that performs Customer Segmentation

Libraries Used
- Numpy
- Pandas
- Matplotlib
- Seaborn
- Scikit learn

Models Trained
- KMeans Clustering
- Hierarchical Clustering
Code for this project can be found here 👇

[Please do consider giving an upvote if you find this notebook to be useful 😀]

kaggle.com/piyalbanik/seg…
1. Business Understanding

The goal of this project is to divide customers into groups based on common characteristics in order to maximize the value of each customer to the business.
Read 13 tweets
Aug 15, 2021
3 remote Data Science and Machine Learning Internship opportunities which are open for all.

🧵👇 Image
1. Graduate Rotational Internship Program - The Sparks Foundation

The Graduate Rotational Internship Program is a unique offer for students and recent graduates to experience and join The Sparks Foundation.

Apply 👇
internship.thesparksfoundation.info
2. Omenda

Omdena AI projects are the best way to build sought-after data science and machine learning skills while solving real-world problems.

Apply 👇
omdena.com/projects/
Read 5 tweets
Aug 12, 2021
3 beginners level Machine Learning projects with code

- Regression
- Classification
- Clustering

🧵👇
Read 5 tweets
Aug 8, 2021
#DataScience Project 3

Best Suburb to Open a Cafeteria in Melbourne 🇦🇺

- Create a Machine Learning model which suggests a location to open a Cafe.

Libraries Used
- Numpy
- Pandas
- Matplotlib
- Scikit Learn
- BeautifulSoup
- Geocoder
- Folium

Model Used:
- K Means Clustering
Please Note: the main focus of this project was on data collection, visualization, and training a model. Did not involve data cleaning.

Code for this project 👇
github.com/Piyal-Banik/Me…
1. Business Understanding:

The main goal of this project is to collect and analyze data in order to select a location in Melbourne to open a Cafeteria. We want to help a business owner planning to open up a Cafe in a location by exploring better facilities around the Suburb.
Read 17 tweets
Jul 26, 2021
Data Science Pipeline

🧵👇
Acknowledgment:

- John Rollins, @IBM

- Data Science Methodology, @coursera
coursera.org/learn/data-sci…
1. Business Understanding: What is the problem that we are trying to solve?

- We should have clarity of what is the exact problem we are going to solve.

- Asking the right questions as a Data Scientist starts with understanding the goal of the business.
Read 13 tweets
Jul 25, 2021
#DataScience Project 1

Titanic – Machine Learning from Disaster

Use Machine Learning to create a model that predicts which passengers survived the Titanic shipwreck.

Libraries Used
- Numpy
- Pandas
- Seaborn
- Sickit-Learn

Final Model Chosen
- Decision Tree: 93.03% accuracy🔥
The data science methodology followed has been outlined by John Rollins, IBM

- Business Understanding
- Analytical Approach
- Data requirements
- Data collection
- Data Understanding
- Data Preparation
- Modeling
- Evaluation

Project Code 👇
github.com/Piyal-Banik/Ti…
1. Business Understanding

Given a passenger's information, how can we predict whether he/she survived the Titanic disaster?

2. Analytical Approach:

Our target variable is categorical [survived / not survived], and hence we need classification models for this task.
Read 15 tweets

Did Thread Reader help you today?

Support us! We are indie developers!


This site is made by just two indie developers on a laptop doing marketing, support and development! Read more about the story.

Become a Premium Member ($3/month or $30/year) and get exclusive features!

Become Premium

Don't want to be a Premium member but still want to support us?

Make a small donation by buying us coffee ($5) or help with server cost ($10)

Donate via Paypal

Or Donate anonymously using crypto!

Ethereum

0xfe58350B80634f60Fa6Dc149a72b4DFbc17D341E copy

Bitcoin

3ATGMxNzCUFzxpMCHL5sWSt4DVtS8UqXpi copy

Thank you for your support!

Follow Us!

:(