PROFILE
4+ Years of IT experience in historic data and apply statistical concepts to make cross-sectional predictions.
Predictive analytics uses many techniques from data mining, statistics, modelling, machine learning and
artificial intelligence to analyze current data to make predictions about future.

SKILLS
Python/ML Packages: NumPy, Pandas, Sci-py, Scikit-learn, Seaborn,
Matplotlib, Flask.
ML: Linear Regression, Ridge & Lasso Regression, Logistic Regression,
Naïve Bayes Classifier, KNN, SVM, Decision Tree, Random Forest,
Gradient Descent, Ada-Boost, Gradient Boosting, XGBoost, K-means

Language Skills
English ■■■■■■■■■■
Hindi ■■■■■■■■■■
Marathi ■■■■■■■■■■

Time-Series Analysis: AR, MA, ARIMA, SARIMA models for time series data analysis.
AWS: Elastic Compute Cloud, Sage maker, Notebook instance, AWS container, Simple Storage Services S3,
Deployment, Multi cloud environment.
Database: SQL, MongoDB, 3C (Command, Constrains, Clauses), CRUD operations, Subqueries, Window
functions, Joins
Deep Learning: Neural Networks, Deep Learning, ANN, CNN, DNN, Transfer Learning, Back Propagation, Linear
Algebra, Activation & loss functions, optimizers, TensorFlow 2.x, Karas.
Maths & Stats: Filter, Wrapper, Embedded Method, P-Value, T-Test, Z-Test, ANNOVA test, Chi-Square Test, Info-
Gain Test, Hypothesis Testing, Probability, statistics, linear algebra, probability, statistics, linear algebra.
NLP: Text understanding, representation & classification techniques, Text clustering skills
Libraries: NLTK, spacy, gensim, text blob, Lang detect, google trans