Sparsh Jaiswal’s Post

🎉 Excited to share another project I completed during my internship at Encryptix ! 🎉 I had the opportunity to develop a model to predict customer churn for a subscription-based service, a vital task for businesses looking to retain their customers. Using historical customer data, including usage behavior and demographics, I experimented with various algorithms to forecast churn rates. Here’s an overview of the project: • Data Analysis: Conducted extensive data preprocessing and exploratory data analysis to uncover trends and correlations in customer behavior. • Algorithm Selection: Evaluated multiple machine learning algorithms to identify the most effective method for predicting churn. • Model Training: Trained and fine-tuned models using Logistic Regression, Random Forests, and Gradient Boosting, assessing their performance based on metrics such as accuracy, precision, recall, and F1 score. • Results: The Gradient Boosting model provided the highest accuracy and reliability in predicting customer churn, enabling better proactive retention strategies. This project was a fantastic learning experience, giving me practical insights into machine learning applications for customer retention. I’m grateful to the Encryptix team for their support and mentorship throughout this project. Looking forward to leveraging these skills in future projects and helping businesses enhance customer loyalty and retention! #MachineLearning #CustomerRetention #ChurnPrediction #DataScience #ArtificialIntelligence #InternshipExperience #Encryptix

🚀 Excited to share that I have successfully completed my first task during my Data Science internship at Encryptix! I developed a model to estimate user ratings for movies. This Movie Rating Prediction project involved comprehensive data analysis, preprocessing, feature engineering, and applying machine learning modeling techniques. I explored various algorithms, fine-tuned hyperparameters, and validated the model to ensure high accuracy. Through this project, I gained valuable insights into handling large datasets, improving model performance, and effectively communicating findings to stakeholders. #DataScience #MachineLearning #DataAnalysis #FeatureEngineering #Encryptix

Exciting update from my internship at Encryptix!  I have successfully completed Task 3 of Sales Prediction. In this study, four distinct regression models were evaluated: Linear Regression, Random Forest Regressor, Decision Tree Regressor, and Gradient Boosting Regressor to predict sales based on TV, Radio and Newspaper advertising budgets. Each model was trained on 80% of the data and tested on the remaining 20%. The performance metrics, Mean Squared Error (MSE) and R^2 Score, were calculated to assess the models' accuracy. The results highlighted the strengths and weaknesses of each approach in predicting sales. Among these, the Gradient Boosting Regressor demonstrated the highest accuracy, with superior MSE and R^2 Score values. Consequently, we selected the Gradient Boosting Regressor for further predictions in the analysis. 🙌 Gratitude to Encryptix for the invaluable learning journey and mentorship. Thrilled to contribute to impactful projects in data science!  Check out the full project on my GitHub: https://lnkd.in/duwpUcHu #DataScience #MachineLearning #SalesPrediction #Encrptix. Encryptix

🚀 Excited to share that I have successfully completed my 3rd task during my Data Science internship at Encryptix ! I developed a model to estimate user ratings for movies. This Movie Rating Prediction project involved comprehensive data analysis, preprocessing, feature engineering, and applying machine learning modeling techniques. I explored various algorithms, fine-tuned hyperparameters, and validated the model to ensure high accuracy. Through this project, I gained valuable insights into handling large datasets, improving model performance, and effectively communicating findings to stakeholders. #DataScience #MachineLearning #DataAnalysis #FeatureEngineering #Encryptix

🚀 Excited to share my internship journey at #Encryptix! 🚀 During my time at Encryptix, I worked on three impactful machine learning projects: 📌Customer Churn Prediction using Logistic Regression: - I developed a model to predict customer churn by leveraging logistic regression. - This involved processing customer demographics and usage data to achieve high accuracy in identifying at-risk customers. - Key insights included factors like tenure, credit score, and estimated salary. 📌Spam SMS Detection using Naive Bayes MultinomialNB: - I built a spam detection model using the Naive Bayes MultinomialNB algorithm. - By converting SMS text data into numerical format with TF-IDF, I achieved reliable spam detection. - The model effectively identified spam messages based on specific keywords and phrases. 📌Credit Card Fraud Detection using Random Forest Classifier: - I created a fraud detection model using the Random Forest Classifier. - This project included handling class imbalance with SMOTE and optimizing model parameters with GridSearchCV. - The result was a robust model that achieved high accuracy in detecting fraudulent transactions. 💡These projects provided me with hands-on experience in data preprocessing, model building, and evaluation, enhancing my skills in machine learning and data science. #MachineLearning #DataScience #AI #CustomerChurn #SpamDetection #FraudDetection #Internship #Encryptix

🚀 Excited to share that I have successfully completed my second task during my Data Science internship at Encryptix! I worked on a Sales Prediction project where I leveraged data analysis, statistical modeling, and machine learning techniques to forecast future sales trends. This project involved preprocessing large datasets, identifying relevant features, and developing predictive models to optimize sales strategies. Additionally, I conducted extensive exploratory data analysis to understand underlying patterns and correlations in the sales data. By collaborating remotely with cross-functional teams, I translated insights from the model into actionable recommendations for improving sales performance and enhancing business outcomes. This hands-on experience has further strengthened my skills in data visualization, model evaluation, and communication of analytical findings. #DataScience #SalesPrediction #MachineLearning #DataAnalysis #Encryptix

I'm thrilled to share that I’ve successfully completed my first task as a Data Science intern at Encryptix! 🎉 For this task, I built a predictive model to determine the survival of passengers on the Titanic 🛳️. This project was an incredible learning experience that deepened my understanding of various concepts in Data Science, including: 🔍 Data Cleaning: Ensuring the dataset was free of errors and ready for analysis. 📊 Data Visualization: Using visual tools to uncover patterns and insights. 🧠 Model Building: Implementing and fine-tuning machine learning models to make accurate predictions. 📈 Evaluation: Assessing the model’s performance and making necessary improvements. A big thank you to the Encryptix team for their guidance and support! 🙏 I'm looking forward to tackling more challenges and further honing my skills in the fascinating world of Data Science. #DataScience #MachineLearning #Internship #TitanicDataset #PredictiveModeling #DataCleaning #DataVisualization #LearningJourney #Encryptix #CareerGrowth

I have successfully completed all 3 task of my virtual internship (by Encryptix) in Machine learning . I did three tasks : 1)Movie classification using TF-IDF using classifiers such as Multinomial Naive Bayes and logistic regression (58.3% accuracy using logistic regression % 51.12% accuracy using Naive bayes). 2)Credit card fraud detection using Logistic Regression, Decision Trees & Random Forests(99.56% accuracy) 3)SMS Spam detection using naive bayes(98.45% accuracy). Here is a video demonstrating all my 3 tasks. Thanks to Encryptix for the opportunity . #encryptix #machinelearning

🔍 Encryptix Internship: Analyzing Churn Rates 🔍 Another exciting challenge I tackled at Encryptix was analyzing customer churn rates. I developed a model that predicts when users are likely to leave, providing actionable insights to help retain them. This project allowed me to dive deep into customer behavior analysis and sharpen my skills in predictive modeling. A big thank you to the Encryptix team for their guidance and support throughout this journey! #DataScience #MachineLearning #ChurnAnalysis #CustomerRetention #Encryptix

🔍 Encryptix Internship: Analyzing Churn Rates 🔍 Another exciting challenge I tackled at Encryptix was analyzing customer churn rates. I developed a model that predicts when users are likely to leave, providing actionable insights to help retain them. This project allowed me to dive deep into customer behavior analysis and sharpen my skills in predictive modeling. A big thank you to the Encryptix team for their guidance and support throughout this journey! #DataScience #MachineLearning #ChurnAnalysis #CustomerRetention #Encryptix