Regression Models - Simple, Multiple and Logistic Regression
Classification Problems using KNN, Decision Trees - Bagging(Random Forest) and Boosting(GBM and Xgboost), Naive Bayes, SVM and Neural Networks.
Unsupervised Learning: PCA, K-means & Hierarchical Clustering.
Model Building: Python (Numpy, Pandas, Scikit-Learn, Theano, Keras, Tensorflow and BeautifulSoup)
Visualization: Python (Matplotlib, Plotly), Kibana (Elastic Search), Tableau
●Experienced Development Engineer having more than 7 years experience of working in the
information technology and services industry.
● Experience of building machine learning and ETL pipelines from scratch and deploying in
● Expertise in using Kafka, Apache Spark , Spark Streaming, MapReduce and Hadoop
● Experience in validation and selection of ensembled machine learning models.
● Experience using machine learning frameworks like H2o , TensorFlow
Areas Being Served
Data Science Expert
Areas of Expertise:
● Machine Learning● Python● ElasticSearch● Anomaly Detection System● CI/CD
● Data Science● Spark● Java● Clo ● DeepLearning ● TimeSeries ● Recommendation
● Django ● Flask
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