About

Chinni Venkata Raju Koviri is a skilled Data Analyst with over 3 years of experience in Data mining and Machine Learning. He possesses expertise in Data preprocessing and preparation, Feature engineering for both structured and unstructured datasets, and generating visualizations. With hands-on experience in Python, R, and Java, he is familiar with working environments like RStudio, Jupyter notebook, and Spyder. Chinni is also well-versed in all formats of sensor data, raw data formats, and data integration with enough experience in Internet of things [IOT]. Chinni's Machine Learning skills include Natural Language processing, classification methods (naive bayes, random forest, Xgboost, SVM), clustering, Topic modeling, Text mining, performance evaluation of algorithms, and Deep Learning (Tensorflow). He has worked with ML/DL Frameworks like TensorFlow, IBM watson, and Openvino(Intel) and devices like Arduino uno, curie, Intel Edison, Galileo, and Intel Gateways. In terms of programming languages, Chinni is proficient in R, Python, C, C++, java, DS, and Nodejs. He has worked with software like Rstudio, Jupyter Notebook, Netbeans, Eclipse, and Android Studio. Chinni's visualization skills include Tableau, ggplot, and matplotlib. He has worked with Python Libraries like Scikit learn, numpy, matplotlib, Pandas, and openCV, and R Libraries like dplyr, e1071, and rpart. Chinni has worked as a Data Analyst at SVB Financial Group and as a Research Software Engineer - Data Analyst at Illinois Institute of Technology. He has also worked as a Data Scientist at Volantsys Analytics Inc. He holds a Nano Degree in Data Analyst from Udacity, a Master's degree in Computer Science with a Data science specialization from Illinois Institute of Technology, and a Bachelor of Technology - BTech in Electrical and Electronics Engineering from Jawaharlal Nehru Technological University, Kakinada. With his relevant experience of 3.68 years, Chinni is an accomplished Data Analyst with a proven track record of delivering high-quality results. His tech stack includes ML, Jupyter, Deep Learning, Tensorflow, SQL, Naive Bayes, SVM, XGBoost, Random Forest, Python, Data Scientist, Research Scientist, OpenCV, NLP, Scikit, Pandas, Integration,