Skills

• Programming language: Python, R, HTML
• Classification algorithms: Logistic regression, K-Nearest Neighbor, SVM, Naive Bayes, Random Forest, Decision tree.
• Regression algorithms: Linear regression Decision tree, Random forest, SVM.
• Clustering: K-mean, Hierarchical.
• Dimensionality reduction: PCA, LDA.
• NLP: Sentimental analysis, TwiPy, TF-IDF, Naïve Bayes.
• Deployment: Flask, HTML.
• Time series analyzing, Quantum computing basics.
• Process improvement: Black belt in SIG SIGMA, Lean Management, 5S, KAIZEN, 8d’s
• Operations management: TQM, TPM, JIT
• Management tools: MS office SAP, Tally, Minitab

• Deep learning Libraries: TensorFlow, Keras, OpenCV.
• DL techniques: DNN, CNN, RNN, LSTM
• Machine learning libraries: Pandas, NumPy, Matplotlib, SciPy, Ski-kit learn, Seaborn, NLTK
• Visualization tools: Tableau, Power Bi
• Database: MySQL, MongoDB
• Big data architecture: Hadoop, Apache Spark
• Statistical analysis: Inferential analysis, EDA, Hypothesis, ANOVA, t-Test, outlier detection, Interquartile range, Sampling and Boxplot
• Object oriented programming language (OOPS)
• Cloud Computing : AWS
• Design Engineering: HYSYS, MATLAB, AUTOCAD, FUSION 360, Solidworks, CENTRIX, Flow modelling, HAZOP