Machine Learning Scientist for past 5years!
Programming Languages: Python | C++ | JAVA SE | C# | Assembly
Databases: MySQL | MongoDB | Spark SQL | Cassandra | BigQuery
Machine Learning Frameworks: Scikit-learn | TensorFlow | Keras | Caffe/Caffe2 | Torch/PyTorch | Cuda | OpenCV | DLib | MATLAB
BIGData Frameworks: Hadoop | SparkMLib/SparkML | Spark Streaming | Kafka | Kubernetes | Elasticsearch | Docker
Version Control: Git, SVN
Domain expertise in ML: Regression (Linear, Logistic, Regularized models - Ridge/Lasso), Decision Trees, Hypothesis Testing (T-test, Chi-Square, Wilcoxon, Cramers-V, Anova etc.), Clustering(K-Means, Hierarchical) , PCA/Factor Analysis, SVM, Random Forest and Decision Tree modules, Gradient Boosting, AdaBoost, XGBoost, Monte Carlo simulations, Deep Learning/Neural Networks (CNNs, RNNs), Stacking/Ensembles, Linear Blending, Grid Search, SGD classifier, Kalman Filter, EM Algorithm, Linear/Stochastic Programming, Denoising Autoencoders, Adagrad, Adam.