Saiprakash Yamsani

I am a passionate Data Science fresher with a strong foundation in data analysis, machine learning, and visualization. Through a structured Data Science training program, I gained hands-on experience in solving real-world problems using Python, SQL, and advanced analytical methods. Core Skills: Data Analysis & Transformation: Python (Pandas, NumPy), SQL, Excel Machine Learning: Linear & Logistic Regression, Decision Trees, Random Forest, Gradient Boosting, KNN, SVM, Clustering (K-Means, Hierarchical), Dimensionality Reduction (PCA) Deep Learning (Basics): Neural Networks using TensorFlow & Keras Model Evaluation & Optimization: Cross-validation, Hyperparameter tuning, Confusion Matrix, ROC-AUC Visualization: Tableau, Matplotlib, Seaborn for building clear and impactful dashboards Statistics & Problem-Solving: Hypothesis testing, Correlation, ANOVA, Probability distributions I enjoy uncovering patterns in data, building predictive models, and transforming insights into actionable strategies. As a fresher, I am eager to contribute my skills, collaborate with industry experts, and grow in data-driven roles where innovation and decision-making are powered by data.