You will get Sentiment Analysis of Airline Tweets with ML & Visual Insights
Project details
You will get an end-to-end Airline Sentiment Analysis system that classifies tweets using Natural Language Processing (NLP) and Machine Learning, along with insightful dashboards or a Streamlit app. With my academic background in Data Science (MSc) and real project experience, I specialize in extracting actionable insights from real-world customer feedback. This project stands out because it not only builds an accurate sentiment classifier but also delivers business-ready reports, explainable visuals, and an optional interactive web interface — all cleanly documented and tailored to your business needs.
Machine Learning Tools
Microsoft Power BI, NLTK, pandas, Python, scikit-learn, TableauWhat's included
| Service Tiers |
Starter
$40
|
Standard
$80
|
Advanced
$130
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 7 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 2 | 4 |
Number of Scenarios | 1 | 2 | 4 |
Number of Graphs/Charts | 40 | 80 | 130 |
Model Validation/Testing | |||
Model Documentation | - | ||
Data Source Connectivity | |||
Source Code |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$20 - $50
Additional Revision
+$15
Additional Graph/Chart
(+ 1 Day)
+$10
Deploy to Streamlit Cloud
(+ 2 Days)
+$30Frequently asked questions
About Eyesly Meribha
Data Scientist
Chennai, India - 11:57 am local time
Overview / Summary:
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MSc Data Science | Certified in Cybersecurity & Deep Learning | 5+ Projects Done
Hi! I’m Eyesly Meribha Johnson Paulraj, a passionate and detail-oriented Data Science professional with a strong foundation in Python, SQL, Machine Learning, and Data Visualization. With real-world experience in building data pipelines, dashboards, and machine learning models, I help businesses uncover insights and make smarter decisions.
What I Do:
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Data Analysis & Dashboarding (Power BI, Tableau, Excel)
Machine Learning & Forecasting Models (Random Forest, ARIMA, ETS, XGBoost)
ETL Pipeline Development (using Airflow, Pandas, PostgreSQL)
Exploratory Data Analysis (EDA) & Data Cleaning
Reporting & KPI Dashboards for Business Stakeholders
Basic Cybersecurity & Risk Assessment Knowledge
Technical Skills:
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Languages: Python, SQL
Data Visualization: Power BI, Tableau, Matplotlib, Seaborn
Machine Learning: scikit-learn, statsmodels, XGBoost, Random Forest
Data Engineering: Pandas, Numpy, Airflow, PostgreSQL
Others: Excel, Git, Jupyter Notebook, Google Colab
My Key Projects:
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Sales Forecasting Project
→ ARIMA, ETS, Random Forest models with Power BI dashboard
→ Automated pipeline from raw data to final predictions.
Credit Card Fraud Detection
→ Trained multiple classifiers (Logistic Regression, Random Forest, XGBoost)
→ Applied PCA and SHAP for model interpretation.
Customer Sentiment Analysis (NLP)
→ Built sentiment classification pipeline using NLP & Machine Learning
→ Deployed insights with dynamic dashboard presentation.
Experience:
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Freelance Data Scientist (Upwork)
→ Helping clients build predictive models and dashboards
Data Engineer – HCMS Pvt. Ltd.
Intern – UNIQ, Jarvis Software, Cloudcredits Technologies
Education:
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MSc Data Science – Swansea University (UK)
BSc Information Technology – Women’s Christian College, India
Certifications: Cybersecurity (Diploma), Deep Learning (OHSC)
Why Work With Me?
Professional & Friendly Communication
Clear Explanations & Clean Code
On-time Delivery with Full Documentation
Open to Long-Term Collaboration
Let’s discuss your project and make your data work smarter for you!
Click the Invite button — I’m ready to help!
Steps for completing your project
After purchasing the project, send requirements so Eyesly Meribha can start the project.
Delivery time starts when Eyesly Meribha receives requirements from you.
Eyesly Meribha works on your project following the steps below.
Revisions may occur after the delivery date.
Review Requirements & Dataset
Verify dataset columns like text, airline, and airline_sentiment, and understand any specific business focus.
Data Cleaning & Preprocessing
Remove mentions, hashtags, symbols, stopwords, and lemmatize tweets to prepare for ML