
Parvesh Dhawan
Technology / Internet
About Parvesh Dhawan:
Hello there! π 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:
π¬ Expertise: I possess a wide range of skills in statistical languages, Machine Learning, Text Analytics, Business Analytics, and Regression Analysis.
π 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.
π Data Visualization: I excel in creating insightful and visually appealing dashboards using tools like Tableau, matplotlib, Seaborn, and ggplot2.
π‘ Machine Learning: My proficiency spans across various machine learning algorithms, including Decision Tree, Random Forest, Linear Regression, Logistic Regression, SVM, KNN, NaΓ―ve Bayes, Regularization, Artificial Neural Network, Gradient Descent, Ensemble Learning, K-mean Clustering, Error Metrics, Cross-Validation, and Performance Tuning.
β³ 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.
π Text Mining: My knowledge extends to Natural Language Processing (NLP), involving NLTK, Tokenization, Vectorization, TF-IDF, Word Clouds, and Sentiment Analysis.
π 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.
πΎ Databases: I have hands-on experience with MongoDB and MySQL for effective data storage and retrieval.
π» Coding Proficiency: I am proficient and comfortable working with Python (Jupyter Notebook) and R (R studio), enabling me to develop robust data-driven solutions.
Β
Experience
Hello there! π 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:
π¬ Expertise: I possess a wide range of skills in statistical languages, Machine Learning, Text Analytics, Business Analytics, and Regression Analysis.
π 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.
π Data Visualization: I excel in creating insightful and visually appealing dashboards using tools like Tableau, matplotlib, Seaborn, and ggplot2.
π‘ Machine Learning: My proficiency spans across various machine learning algorithms, including Decision Tree, Random Forest, Linear Regression, Logistic Regression, SVM, KNN, NaΓ―ve Bayes, Regularization, Artificial Neural Network, Gradient Descent, Ensemble Learning, K-mean Clustering, Error Metrics, Cross-Validation, and Performance Tuning.
β³ 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.
π Text Mining: My knowledge extends to Natural Language Processing (NLP), involving NLTK, Tokenization, Vectorization, TF-IDF, Word Clouds, and Sentiment Analysis.
π 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.
πΎ Databases: I have hands-on experience with MongoDB and MySQL for effective data storage and retrieval.
π» Coding Proficiency: I am proficient and comfortable working with Python (Jupyter Notebook) and R (R studio), enabling me to develop robust data-driven solutions.
Education
I have completed my Graduation in 2016
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