Parvesh Dhawan

Hello there! 👋 I am a passionate Data Science enthusiast with over 4+ years of practical & Industry driven experience, and I thrive on solving complex problems using data-driven approaches. I am currently in high demand for my expertise in various areas of Data Science. Here's a glimpse of my skillsets and professional journey:

🔬 Expertise: I possess a wide range of skills in statistical languages, Machine Learning, Text Analytics, Business Analytics, and Regression Analysis.

🚀 Experience: I have successfully contributed to diverse projects, both during my internships and in my professional career, primarily in the Maritime Domain. My passion for Data Science extends beyond regular work, and I actively participate in Kaggle, Edwisor, and Freelance projects, as well as other platforms.

📊 Data Visualization: I excel in creating insightful and visually appealing dashboards using tools like Tableau, matplotlib, Seaborn, and ggplot2.

💡 Machine Learning: My proficiency spans across various machine learning algorithms, including Decision Tree, Random Forest, Linear Regression, Logistic Regression, SVM, KNN, Naïve Bayes, Regularization, Artificial Neural Network, Gradient Descent, Ensemble Learning, K-mean Clustering, Error Metrics, Cross-Validation, and Performance Tuning.

⏳ Time Series Analysis: I have a strong grasp of Time Series Modeling, encompassing Statistical Models, Auto Regressive, Moving Averages, ARIMA, SARIMA, FB prophet, Holt Winter, Exponential Smoothing, and Feature Extraction, with expertise in LSTM.

📝 Text Mining: My knowledge extends to Natural Language Processing (NLP), involving NLTK, Tokenization, Vectorization, TF-IDF, Word Clouds, and Sentiment Analysis.

📈 Statistics: I am skilled in Summarizing Data, Understanding Normal Distribution, Sampling, Sample Distributions, Hypothesis Testing, Regression and Correlation, Multi-Collinearity, Chi-square tests, ANOVA, Standardization/Z-score, and Normalization.

💾 Databases: I have hands-on experience with MongoDB and MySQL for effective data storage and retrieval.

💻 Coding Proficiency: I am proficient and comfortable working with Python (Jupyter Notebook) and R (R studio), enabling me to develop robust data-driven solutions.
 

Hello there! 👋 I am a passionate Data Science enthusiast with over 4+ years of practical & Industry driven experience, and I thrive on solving complex problems using data-driven approaches. I am currently in high demand for my expertise in various areas of Data Science. Here's a glimpse of my skillsets and professional journey:

🔬 Expertise: I possess a wide range of skills in statistical languages, Machine Learning, Text Analytics, Business Analytics, and Regression Analysis.

🚀 Experience: I have successfully contributed to diverse projects, both during my internships and in my professional career, primarily in the Maritime Domain. My passion for Data Science extends beyond regular work, and I actively participate in Kaggle, Edwisor, and Freelance projects, as well as other platforms.

📊 Data Visualization: I excel in creating insightful and visually appealing dashboards using tools like Tableau, matplotlib, Seaborn, and ggplot2.

💡 Machine Learning: My proficiency spans across various machine learning algorithms, including Decision Tree, Random Forest, Linear Regression, Logistic Regression, SVM, KNN, Naïve Bayes, Regularization, Artificial Neural Network, Gradient Descent, Ensemble Learning, K-mean Clustering, Error Metrics, Cross-Validation, and Performance Tuning.

⏳ Time Series Analysis: I have a strong grasp of Time Series Modeling, encompassing Statistical Models, Auto Regressive, Moving Averages, ARIMA, SARIMA, FB prophet, Holt Winter, Exponential Smoothing, and Feature Extraction, with expertise in LSTM.

📝 Text Mining: My knowledge extends to Natural Language Processing (NLP), involving NLTK, Tokenization, Vectorization, TF-IDF, Word Clouds, and Sentiment Analysis.

📈 Statistics: I am skilled in Summarizing Data, Understanding Normal Distribution, Sampling, Sample Distributions, Hypothesis Testing, Regression and Correlation, Multi-Collinearity, Chi-square tests, ANOVA, Standardization/Z-score, and Normalization.

💾 Databases: I have hands-on experience with MongoDB and MySQL for effective data storage and retrieval.

💻 Coding Proficiency: I am proficient and comfortable working with Python (Jupyter Notebook) and R (R studio), enabling me to develop robust data-driven solutions.

I have completed my Graduation in 2016