BOMMINENI SUJAN SIDDARTH’s Post

Greetings connections, I am pleased to announce the successful #completion of my one-month internship in the Machine Learning domain at Bharat Intern. During this time, I gained valuable #experience in the field and #successfully completed all tasks within the given #deadlines. Here are my submissions link: Task 1: https://lnkd.in/dReYvHwg Task 2: https://lnkd.in/deK4hepJ #learning #learningandgrowing #developerlife #developercommunity #developement #machinelearning #modeling #python #pythonprogramming #jupyternotebook #intern #internship #github #githubproject #versioncontrol

🌠 I'm excited to share that I've completed Task 4 of my Data Science internship at Prodigy InfoTech! 💥 In this task, I analyzed and visualized sentiment patterns in social media data, uncovering public opinion and attitudes toward various texts and hashtags across different platforms. I also identified clusters of positive and negative sentiments related to texts and social media platforms. All of this was accomplished using Jupyter Notebook for data processing and visualization. 📊  #ProdigyInfoTech #DataScience #Internship #DataVisualization #Python #SentimentAnalysis #EDA 👉 GitHub Link: https://lnkd.in/g9WBgKy7

🌟 Exciting Milestone: Completed My 2nd Project of Internship! 🌟 I'm thrilled to share that I have successfully completed my second project during my internship. The challenge was to perform data cleaning and exploratory data analysis (EDA) on a dataset of my choice. I chose the well-known Titanic dataset from Kaggle. 🔍 Problem Statement: Perform data cleaning and exploratory data analysis (EDA) on the Titanic dataset. The goal was to explore relationships between variables and identify patterns and trends in the data. Prodigy InfoTech #DataScience #Internship #EDA #DataCleaning #TitanicDataset #LearningJourney #Kaggle #Python #DataAnalysis #Visualization Github link:

Exciting News! Thrilled to share that during my internship at Prodigy InfoTech, I've successfully completed and launched a CUSTOMER SEGMENTATION PROJECT using Jupyter Lab Notebook! [ TASK 1 OF THE INTERNSHIP] Key Highlights: Utilized advanced data science techniques to segment customers effectively. Leveraged Python programming and popular libraries such as Pandas, NumPy, and Scikit-learn. Conducted exploratory data analysis to understand customer behavior and preferences. Implemented clustering algorithms to identify distinct customer groups. Visualized insights using Matplotlib and Seaborn for clear and intuitive understanding. This project has been an incredible learning experience, allowing me to apply my data science skills in a real-world scenario and deliver actionable insights for business growth. A big shoutout to my mentors and the Tech-A-Intern team for their guidance and support throughout this journey! 🙌 Looking forward to more exciting challenges ahead! 🌟 #DataScience #CustomerSegmentation #JupyterLab #TechAIntern #Internship #DataAnalytics #PythonProgramming Feel free to check out the project or connect with me on LinkedIn to learn more! 👇🔗 GIT HUB LINK- https://lnkd.in/e4_iynhb

I am excited to announce that I have successfully completed Task 1 of my Data Science Internship at Prodigy Infotech! Task Details: - **Topic**: Creating a Bar Chart or Histogram - **Task**: Create a bar chart or histogram to visualize the distribution of a categorical or continuous variable, such as the distribution of ages or genders in a population. Check out my work on GitHub at: https://lnkd.in/eJVG7Djp #DataScience #Internship #ProdigyInfotech #Visualization #Python #Matplotlib #Seaborn #GitHub

Task 3 Submission : Internship at Prodigy InfoTech 🔍 Task Overview: Build a decision tree classifier to predict whether a customer will purchase a product or service based on their demographic and behavioral data. Use a dataset such as the Bank Marketing dataset from the UCI Machine Learning Repository. 👉 IDE Used: Jupyter Notebook with Python3 👉 Steps Performed: ✔ Data Loading using Python Libraries ✔ Data Extraction & Cleaning ✔ Exploratory data analysis ✔ Data Transformation ✔ Results 👉 Key Learnings: ✔ Loading, manipulating and visualizing data using python libraries such as pandas, matplotlib and seaborn. ✔ Understanding relationships between the data and visualising them to find some meaningful insights. ✔ Split the dataset into training and validation sets.Trained a decision tree classifier using scikit-learn. ✔ Evaluated the model's performance on a validation set using Accuracy score.   👉 GitHub Repository link: https://lnkd.in/geE5KcDe Thanks to Prodigy InfoTech for providing this opportunity. #internshipexperience #prodigyinfotech 

🚀 Excited to share that I've completed Task 2 of my Data Science internship at Prodigy InfoTech! 📊 Task 2 involved performing data cleaning and exploratory data analysis (EDA) on a dataset of my choice. I chose the Titanic dataset from Kaggle for this task. 🔍 Using Python in Jupyter Notebook, I explored the relationships between variables, identified patterns and trends, and visualized the data to gain insights. It was a valuable experience in understanding the importance of thorough data cleaning and EDA in any data science project. 🔗GitHub Link: https://lnkd.in/eNtmFTAp #DataScience #Internship #ProdigyInfotech

Task 1 Completed!As part of my internship with Prodigy Infotech, I'm excited to share my first task: Visualizing the distribution of a categorical variable using a Bar Chart. 📊Using Python in Jupyter Notebook, I explored the relationship between variables. This visualization provides valuable insights into the composition of the population, helping us better understand trends and patterns.Stay tuned for my next tasks!#ProdigyInfotech #Internship #DataVisualization #BarChart #DataAnalysis https://lnkd.in/dGYDMZCA

Thrilled to share the exciting developments during my internship at Prodigy InfoTech. I'm excited to reveal the outcomes of my recent project, where I skillfully derived accuracy using decision tree. In this task3, I build a decision tree classifier using dataset to predict whether a customer will purchase a product or service based on their demographic and behavioral data GITHUB LINK- https://lnkd.in/gG-T5MTm #prodigyinfotech #intern #datascience #machinelearning #decisiontree #predictiveanalysis #python #marketinganalysis #UCIREPOSITORY

Task 4 Submission : Internship at Prodigy InfoTech 🔍 Task Overview: Analyze and visualize sentiment patterns in social media data to understand public opinion and attitudes towards specific topics or brands. 👉 IDE Used: Jupyter Notebook with Python3 👉 Steps Performed: ✔ Data Loading using Python Libraries ✔ Data Extraction & Cleaning ✔ Exploratory data analysis ✔ Results 👉 Key Learnings: ✔ Loading, manipulating and visualizing data using python libraries such as pandas, matplotlib and seaborn. ✔ Understanding relationships between the data and visualising them to find some meaningful insights. ✔ Analyze and visualize sentiment patterns in social media data to understand public opinion ✔ Evaluated the model's performance on a validation set using Accuracy score.   👉 GitHub Repository link: https://lnkd.in/gDA4GMYZ Thanks to Prodigy InfoTech for providing this opportunity. #internshipexperience #prodigyinfotech