Online_Shopping_Sentiment_Analaysis_Flipkart

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Online_Shopping_Sentiment_Analaysis_Flipkart

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This project focuses on sentiment analysis of customer reviews on the Flipkart e-commerce platform. Leveraging natural language processing (NLP) and machine learning algorithms, we aim to extract valuable insights into user sentiments, providing a comprehensive understanding of their experiences and preferences.

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# Global Core Tech Internship - Data Science with Python

Welcome to the Global Core Tech Internship on Data Science with Python! This four-week internship program, from October 26th to November 24th, is designed to equip you with the essential skills and knowledge in data science using Python, with a focus on libraries such as NumPy, Pandas, Matplotlib, and exploratory data analysis (EDA).

## Table of Contents

1. [**Prerequisites**](#prerequisites)
    - [Python 3.7 Installation](#python-370-installation)
    - [Setting up the Environment](#setting-up-the-environment)
2. [**Getting Started**](#getting-started)
    - [Verifying Python Installation](#verifying-python-installation)
    - [Installing Libraries](#installing-libraries)
3. [**Exploratory Data Analysis (EDA)**](#exploratory-data-analysis-eda)
4. [**Learning Resources**](#learning-resources)
5. [**Projects**](#projects)

## Prerequisites

### Python 3.7 Installation

We'll start by setting up Python 3.7, which is the version we'll be using for this internship.

1. Download Python 3.7 from [python.org](https://www.python.org/downloads/windows/).
2. Run the Windows x86-64 executable installer.
3. During installation, make sure to:
   - Add Python 3.7 to your system PATH by ticking the corresponding option.
   - Select "Install launcher for all users" and "Add Python 3.7 to PATH".
4. Complete the installation process, and ensure that Python 3.7 is installed by opening a command prompt (Win+R, type `cmd`, press Enter) and running:
   ```
   python --version
   ```

### Setting up the Environment

To ensure the correct environment configuration, follow these steps:

1. Open a command prompt and execute the following command to set the PATH:
   ```
   set PATH=%PATH%;C:\Program Files\Python3
   ```
2. Edit your system variables by adding `C:\Program Files\Python3` to the `PATH` variable.
3. Verify the Python version again by running:
   ```
   python --version
   ```

## Getting Started

### Verifying Python Installation

Make sure Python 3.7 is installed by running the following command in the command prompt:

```bash
python --version
```

### Installing Libraries

Install the required Python libraries (NumPy, Pandas, Matplotlib, Seaborn, and Plotly) using pip:

```bash
pip install numpy pandas matplotlib seaborn plotly
```

After installation, close the command prompt.

### Verifying Library Installation

To verify that the libraries are installed correctly, open the Python IDLE for Python 3.7.0 and run the following commands:

```python
import pip
import numpy
import pandas
import matplotlib
import seaborn
import plotly
```

## Exploratory Data Analysis (EDA)

Explore and analyze data by using the libraries you've just installed. Perform data analysis, visualization, and gain insights from your datasets.

## Learning Resources

As you progress through the internship, you can enhance your knowledge and skills through various online platforms and resources, including:

- [Jovian](https://jovian.ai/)
- [Kaggle](https://www.kaggle.com/)
- [Codecademy](https://www.codecademy.com/)
- [HackerRank](https://www.hackerrank.com/)
- [InterviewBit](https://www.interviewbit.com/)
- [Coding Ninjas](https://www.codingninjas.com/)
- [W3Schools](https://www.w3schools.com/)
- [LeetCode](https://leetcode.com/)
- [Codechef](https://www.codechef.com/)
- [Scaler](https://www.scaler.com/)
- [GitHub](https://github.com/)

You can also refer to the book "Tutorial 3.7: Python from Beginner to Advanced" to deepen your Python knowledge.

## Projects

During this internship, you will have the opportunity to execute and work on data science projects in Jupyter Notebook using Python 3.7.0. One of the projects you'll be working on is the **Online Shopping Sentiment Analysis Project: Flipkart**.

### Online Shopping Sentiment Analysis Project: Flipkart

- **Project Description**: In this project, you will delve into the world of sentiment analysis in the context of online shopping reviews on Flipkart, a popular e-commerce platform. You will analyze and classify customer reviews into positive, negative, or neutral sentiments, providing valuable insights for both consumers and businesses.

- **Project Goals**:
  - Collect and preprocess data from Flipkart reviews.
  - Perform text analysis and sentiment classification using Python and data science libraries.
  - Create visualizations to present your findings effectively.
  - Draw conclusions and make recommendations based on the sentiment analysis results.

This project is an excellent opportunity to apply the knowledge and skills you've gained during the internship to a real-world data science scenario. It will also give you a chance to showcase your abilities as a data scientist.

Feel free to reach out to mentors and fellow interns for guidance and support as you work on the **Online Shopping Sentiment Analysis Project: Flipkart** during your internship.

Online_Shopping_Sentiment_Analaysis_Flipkart

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