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Data Science Enthusiast 🤞🕵️ Play with Data ;) Studying at Krishna Engineering College📚
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InternAcademy
August 11, 2021 – August 11, 2021
This Repository contains all my work done at The Intern Academy as a Data Science Intern
View ProjectLetsUpgrade-Python-Essentials
July 21, 2020 – July 28, 2020
Assignment solution of Core Python Course by LetsUpgrade
View ProjectLetsUpgrade-AI-ML
July 8, 2020 – June 16, 2021
Course Assignments for the AI/ML course by LetsUpgrade
View ProjectKaggle_Titanic_Survival_Prediction
July 3, 2020 – August 11, 2021
Create and Train Logistic Regression Model which predicts whether a given passenger survived or not
View ProjectImage_Classification
July 1, 2020 – August 11, 2021
Create and Train Logistic Regression, Decision Tree, Naive Bayes which is able to predict given hand-written digits images (mnist 784) and find the model that will able to distinguish between images with a very highest accuracy over other Algorithms
View ProjectTwitter_review_Sentiment_Analysis
July 1, 2020 – July 3, 2020
Apply the logistic regression classification algorithm using scikit-learn and Python to classify Twitter reviews as either postive or negative.
View ProjectUnivariate_linear_regression
June 20, 2020 – June 23, 2020
Implementing the gradient descent algorithm from scratch and performing univariate linear regression with Numpy and Python and visualizing data and plots using matplotlib. [ Project done on Coursera Project Network ]
View ProjectCultural Fit Analysis
The candidate's projects are primarily personal and academic, focusing on Machine Learning and Data Science. While these demonstrate initiative, the direct alignment with a general 'Software Engineer' role is limited without more diverse software development projects. The breadth of skills is narrow, heavily concentrated on Python and ML libraries. The candidate's experience level is 0, indicating an entry-level profile.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback provided.