Pankaj Kumar’s Post

🚀 Excited to Share My Progress! 🚀 I’ve just completed my second task in the TechnoHacks EduTech Official Data Science Internship — "Fraud Transaction Detection." 🕵️♂️💻 🔍 During this task, I worked on developing a machine learning model to detect fraudulent transactions, a critical real-world application of data science. I utilized techniques like data preprocessing, feature engineering, and algorithm tuning to achieve reliable and accurate results. On to the next challenge! 🚀 #DataScience #FraudDetection #MachineLearning #Technohacks #AI #InternshipExperience #Python #Innovation #LearningJourney

Hello everyone! Just wrapped up my first task as a Machine Learning intern at Codeway! 🎬 Project Title: Movie Genre Classification Task: Built a machine learning model to classify a movie's genre based on its textual description. Steps Followed: 1. Data Collection: Gathered movie data from Kaggle to create a comprehensive dataset. 2. Data Processing: Ensured clarity and efficiency by preprocessing textual descriptions. 3. EDA and Visualization: Conducted exploratory data analysis, gaining insights and used graphical visualizations for a deeper understanding. 4. Model Selection: Implemented the NLTK library and Naive Bayes algorithm to capture nuances in movie genres effectively. 5. Model Training: Trained the selected model on processed data for accurate genre classification. 6. Model Evaluation: Rigorously assessed the model's performance, ensuring reliability and accuracy. 🌟 Outcome: Successfully developed a model, incorporating Naive Bayes, that provides accurate genre classification for movies. Excited about this achievement and ready for the next challenges in the realm of Machine Learning! #MachineLearningIntern #CodewayJourney #CODEWAY

Thrilled to share that I've successfully completed Task 3 of the Code Ways ML internship, focusing on Customer Churn Prediction. In this project, I delved into the fascinating world of machine learning to predict customer churn. Leveraging cutting-edge techniques and tools, I analyzed data patterns and built a robust model to forecast customer behavior. github link-https://lnkd.in/gds4qTeH #MachineLearning #codeway #codewayintern

#Hello Connections 👋🌟 I'm excited to share that I've completed my 5th task during my internship at CodSoft Task -5: Credit Card fraud detection As financial fraud becomes increasingly sophisticated, the need for advanced detection methods is more critical than ever. This project aims to enhance the security of credit card transactions by implementing cutting-edge machine learning techniques. 🔹 Project Highlights: 1)Objective: Create a high-accuracy model that detects fraudulent transactions in real-time. 2)Tech Stack: Leveraging Python, TensorFlow, and Scikit-Learn for powerful machine learning capabilities. 3)Methodology: Employing supervised learning, feature engineering, and anomaly detection to optimize precision and recall. 4)Impact: Reducing financial losses and increasing consumer trust in digital payments. I'm passionate about this project because it addresses a real-world problem with significant implications for financial security. Stay tuned for more updates as I continue to develop and refine this model. #MachineLearning #DataScience #CreditCardFraud #CodSoft #AI #Project  P.S. Check out the video for a deeper dive! Github repository for this task: https://lnkd.in/e3FmauAH

🚀 Excited to share that I've completed my machine learning internship at Codeway Solutions🎉 Learned Various techniques & Completed 3 projects with key insights: 📝 Movie Genre Classification Utilized TF-IDF and classifiers such as Naive Bayes. 📊 Credit Card Fraud Detection Employed Logistic Regression and Random Forests. 📈 Customer Churn Prediction Utilized Random Forests and Gradient Boosting. #CODEWAY #MachineLearning #InternshipSuccess #DataScience #AI #ML #CodewaySolutions 🤖💼

Excited to share my latest project for Intern/Prodigy 💻✨ Dive into the code and see how I classified Dogs and Cats images using various family of CNN models. Grateful for the opportunity to apply my skills and learn in a real-world setting. #Coding #ProdigyInfoTech" I have trained using different CNN models and classification of image data is done using SVM(Support Vector Machine). The below picture depicts the accuracy's of different models.

🚀 Thrilled to unveil Task 1 of My CodSoft Machine Learning Internship: The Credit Card Fraud Detection Project! 🌐 Leveraging a rich palette of ML algorithms—logistic regression, decision trees, random forests, XGBoost, SVM, and naive Bayes—I've meticulously crafted models to discern and thwart fraudulent transactions. Task 1 is more than just lines of code; it's a dedication to financial security, minimizing losses, and fortifying confidence in credit card transactions. The journey includes exhaustive data exploration, preprocessing, and model evaluation, striking an optimal balance between precision and recall. Dive into the intricacies of the project on GitHub: https://lnkd.in/gunQuCKh 💻💳 Ready to embark on this ML adventure with CodeSoft! #CodeSoftIntern #MachineLearning #DataScience #FraudDetection #CreditCardSecurity #GitHubProject

Exciting news! Just completed my Data Science internship at CodeClause ! During my time there, I worked on multiple projects, including speech and emotion recognition predictive models and loan prediction. Check out my portfolio in bio for more details. #internshipcompletion #datascience #skillbuilding #projectcompletion #ai #dataanalytics #DataScience #InternLife #CareerGoals #TechIndustry #DataDriven #Analytics #STEM #FutureofWork #DataSkills #ProfessionalDevelopment #CodingCommunity #TechSkills #CareerJourney #DataScienceWorld #Innovation #TechTrends #codeclause

Excited to have successfully completed my internship with CODTECH IT SOLUTIONS , where I focused on Data Analytics tasks. Task 1: Fraud Detection in Financial Transactions Project: Credit Card Fraud Detection The objective of this project was to develop a model to detect fraudulent credit card transactions. The goal was to use various machine learning algorithms to classify transactions as fraudulent or legitimate, thereby helping financial institutions minimize losses. Key Activities: - Data Preprocessing: Cleaned and prepared the dataset by handling missing values, outliers, and imbalanced classes. - Feature Engineering: Created new features from existing data to improve model performance. - Model Training: Built and trained various machine learning models (e.g., Logistic Regression, Random Forest, Neural Networks). - Model Evaluation: Evaluated model performance using metrics such as accuracy, precision, recall, and F1-score. Technologies Used: - Python: The primary programming language for data analysis. - pandas: Used for data manipulation and analysis. - scikit-learn: For implementing machine learning algorithms. - matplotlib & seaborn: For data visualization. These tasks provided me with practical experience in fraud detection, machine learning model training, and model evaluation. #Internship #DataAnalytics #DataScience #MachineLearning #FraudDetection #CODTECH #Python #CareerGrowth

Hello everyone! ✨Second task complete✨ I am thrilled to announce that I have successfully completed✅️ the second task assigned to me as a Data Science intern 👨🏻💻 at CodeClause . The task was to devise a model to perform 'Wine Quality Prediction'🍷. ML models used: SVC and Logistic Regression Dataset source: Kaggle Link to the project code: https://lnkd.in/gdYEx5VM #datascience #codeclause #codeclauseinternship #datascienceinternship #winequalityprediction #machinelearning