About Me

 I have good conceptual and applied knowledge in Machine learning, Deep learning, Natural language processing, Computer vision, Data visualization, Data structures, and algorithms. I am well versed with different frameworks like TensorFlow, MxNet..., Data structures, and algorithms. I am well versed with different frameworks like TensorFlow, MxNet, Theano, Caffe, Torch & Keras and also good proficiency in programming languages like Python & C.

I have done several projects on data science with different kinds of data, both structured and unstructured. I have done projects for parsing unstructured data with different file formats and also build a conversational AI bot. I can efficiently build and deploy Machine learning and Deep learning models in the cloud or non-cloud infrastructures. I have experience with AWS and spark for handling large datasets and build Scalable and robust models.

My master's final year project was under the soft-computing domain. I had done a lot of research and developed an algorithm for solving multi-attribute decision-making problems using probabilistic interval-valued intuitionistic hesitant fuzzy set and PSO. My project paper got accepted in NOIEAS conference 2019 held at NIT Warangal. It is going to be published by Springer Publication coming month.

Professional Skills
1. Data mining, Data wrangling, Data visualization, Predictive modeling.
2. ML Algorithms: KNN, K-means, Decision-Trees, SVM, Naive-Bayes, etc
3. Neural networks: CNN, RNN, GRU, etc.
4. NLP: Word2vec, Glove, Tf-IDF, etc.
5. ML libraries: Numpy, Pandas, Scikitlearn, Opencv, MLlib, Spacy, Pillow, etc.
6. Frameworks: Tensorflow, Mxnet, Caffe, Pytorch, Keras.
7. Big data: Spark and Hadoop.
8. Programming languages: C & Python.
9. Quick learning skills, decision making, and excellent team spirit.