I have already worked with keras for image analytics part including classification and segmentation
I'm a 'Numbers' guy. I'm pursuing my career as a Lead data Scientist, with core expertise in architecting, pipelining and building Machine Learning based solutions. I love data and Insights it provides. My work has revolved architecting ML-driven solutions in products/platforms and getting them live into production. My expertise is XGBoost, RandomForest, kNN, NaiveBayes, SVM, Neural Networks, Deep Learning, LSTM, CNN, Machine vision, Memory Networks,Seq2Seq, Auto-encoders and Logistic Regression, etc. applying them on a variety of datasets and problem statements. I use Tensorflow, Pytorch, Keras, Spark core and MLib, H2o as ML Frameworks. I use Python (Jupyter Notebook) for most of my work. Git for maintaining codes and GCP/AWS when there's need for high computing power! Have worked with Big data, Hive, Hadoop for data storage and querying. Tableau dashboards. Flask for APIs for model serving. Spark for distributed computing. I truly believe that stitching together various ML/DL algorithm with ML/DL techniques and making trade off between compute power and accuracy,we can solve many business problems.