1stop-Keep-Growing-Internship

📊 Data Science Internship at 1Stop|Keep Growing

🏢 About the Internship

I completed an intensive Data Science Internship at 1Stop Keep Growing Company, where I underwent industrial training and participated in live classes designed to strengthen my practical knowledge in data science, project development, and deployment. This hands-on experience provided me with a solid foundation in real-world applications of data science concepts and methodologies.

🧠 Skills and Tools Gained

• Python Programming for Data Science
• Data Preprocessing and Cleaning
• Exploratory Data Analysis (EDA)
• Machine Learning Model Building
• Evaluation Metrics and Model Validation
• NLP (Natural Language Processing)
• Use of libraries: Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn
• Problem-solving with real-world datasets

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🛠️ Projects Completed

📌 Internship Project: Hate Speech Detection

• Objective: Detect and classify hate speech in social media text using Natural Language Processing (NLP).

• Key Techniques:

  • Text preprocessing (tokenization, stopword removal, etc.)
  • Feature extraction using TF-IDF
  • Classification using Logistic Regression, Naive Bayes
  • Model evaluation with accuracy, precision, recall

• Outcome: Built an efficient binary classifier to detect hate speech with high accuracy.

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📌 Project 1: Predicting Mortality of Heart Failure Patients

• Objective: Predict the likelihood of death events in heart failure patients using clinical features.

• Key Techniques:

  • Data analysis and visualization
  • Feature selection and correlation analysis
  • Supervised machine learning (Random Forest, Logistic Regression)
  • ROC Curve and AUC for performance measurement

• Outcome: Developed a reliable prediction model to assist in healthcare risk assessment.

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📌 Project 2: Credit EDA

• Objective: Perform Exploratory Data Analysis (EDA) on a credit dataset to extract insights and patterns.

• Key Techniques:

  • Handling missing values and data cleaning
  • Univariate and bivariate analysis
  • Correlation heatmaps and visual storytelling
  • Identification of customer behavior trends

• Outcome: Delivered a comprehensive EDA report that highlights customer credit patterns and risk factors.

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🚀 Takeaways

• Real-time project exposure and teamwork
• Stronger understanding of data science workflows
• Enhanced coding and analytical abilities
• Improved communication through project presentations and live interactions

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