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...
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.
Skills
Web Development
Data & Analytics
Database
Programming Language
Others
Portfolio Projects
Company
Bank products recommendation to the customers using the concept of multilabel classification.
Description
Built a bank products recommendation to the customers using the concept of multilabel classification for one of a banking clients of Cognizant. Different multilabel classifiers are used for predictions and get good results using OneVsRestClassifier with Random Forest.
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Python Machine Learning Apache Spark DjangoCompany
Conversational chatbot with Rasa Stack and Python-Rasa NLU.
Description
Conversational chatbot with Rasa Stack and Python-Rasa NLU for one of clients of Cognizant. Their use case was to have a chatbot for site engineers or customers to get resolution for any problems with any of the parts of tractors and trucks the company provides, based on any image or text they provide .
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Designed an algorithm for solving Multi-attribute Decision-making problems using Probabilistic Inter
Description
Designed an algorithm for solving Multi-attribute Decision-making problems using Probabilistic Interval-Valued Intuitionistic Hesitant Fuzzy set and PSO. (Accepted for publication in the lecture series entitled “Advances in Intelligent Systems and Computing (SCOPUS) by SPRINGER PUBLICATIONS”).
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Fuzzy Logic PythonTools
Python