Hrishikesh Phapale Email

Hrishikesh Phapale Skills

• AWS SageMaker
• Advanced plotting with seaborn
• Aggregating data and grouping
• Analitical
• Analytical Skills
• Analytics
• Artificial Intelligence (AI)
• Attention to Detail
• Autodesk Fusion 360
• Basic understanding of Big Data tools (Hadoop, Spark)
• Business Analytics
• Communication and presentation skills for explaining data insights
• Computer Science
• Creating dynamic charts in Excel
• Creating heatmaps, boxplots, and scatter plots
• Creating static plots (e.g., bar plots, histograms) using matplotlib
• Dashboarding with Dash and Plotly
• Data Analysis
• Data Cleaning
• Data Modeling
• Data Science
• Data Visualization
• Data cleaning and preprocessing
• Data cleaning and preprocessing in pandas
• Data visualization principles (e.g., clarity, simplicity)
• Data wrangling using pandas in Python
• Databases
• Deep Learning
• Deep Learning (TensorFlow/Keras)
• Descriptive Analysis
• Evaluating models using cross-validation
• Feature Selection
• Feature engineering techniques
• Feature selection techniques
• Git
• Guest Experience
• Handling missing data
• Hyperparameter tuning and model selection
• Hyperparameter tuning with grid search or random search
• Image Processing (OpenCV)
• Image classification using CNNs
• Implementing decision trees and random forests
• Interactive visualizations using Plotly
• K-Nearest Neighbors (KNN)
• Keras
• Leadership
• Linear regression and logistic regression
• Logistic Regression
• Luxury Sales
• MLOps
• Machine Learning (Scikit-learn)
• Merging and joining datasets
• Microsoft Excel
• Microsoft Power BI
• Modeling
• Naive Bayes classifiers
• Natural Language Processing (NLP) basics
• Neuro-Linguistic Programming (NLP)
• Normalization and scaling data (e.g., Min-Max Scaling)
• Overfitting and underfitting prevention
• Problem Solving
• Programming Languages
• Python (Programming Language)
• Python libraries for data analysis (e.g., pandas, numpy)
• Python programming for data science
• Quantitative Analytics
• Quantitative Research
• Recurrent Neural Networks (RNNs) for time series and sequence data
• Retail Sales Analysis
• SQL
• Sales and Marketing
• Scikit-Learn
• Storytelling with data visualization
• Support vector machines (SVM)
• Tableau
• Team Management
• Teamwork
• Technical Proficiency
• TensorFlow
• Time Management
• Time series analysis and forecasting
• Transfer learning with pre-trained models
• Understanding supervised learning (classification, regression)
• Understanding unsupervised learning (clustering, dimensionality reduction)
• Using Tableau for interactive visualization
• Version control with Git and GitHub
• Visualizing correlations and distributions
• Working with pipelines in scikit-learn
• Writing efficient Python code for data manipulation
• k-means clustering
• streamlit