About

Hemant Kumar is a Senior Analyst-Machine Learning Engineer at Tiger Analytics with a passion for exploring and learning new technologies. With 2.86 years of relevant experience, Hemant has developed a strong skill set in various regression, classification, and clustering Machine Learning algorithms. He has hands-on experience with tools such as Logistic Regression, KNN, Support Vector Machine (SVM), Naive Bayes, Decision Tree, Random Forest, XGboost, GBDT, Linear Regression, KMeans clustering, Hierarchical clustering, and DBSCAN. Hemant's expertise extends beyond Machine Learning, as he also has experience in Statistics, Natural Language Processing, and Deep Learning. He has worked with frameworks such as TensorFlow and Keras, pre-trained CNN models like VGG16 and ResNet, and neural network architectures such as ANN, DNN, RNN, and LSTM. Hemant is also skilled in Transfer Learning and proficient in programming languages like Python. In addition to his technical skills, Hemant has experience in data cleaning, data visualization, feature engineering, and exploratory data analysis. He has worked on various projects throughout his career, including validating features like Fast-log, MDNS-SD, ZTP, and Job Scheduler at Infosys. Hemant has also worked on the Usage Billing System project, a web application that generates real-time data usage for clients and calculates the total amount to be paid at the end of the month. Hemant has a Bachelor of Technology in Computer Science from Maulana Abul Kalam Azad University of Technology, West Bengal, formerly WBUT. He also has an Intermediate degree in Science from Bharatiya Vidya Bhavan's. Hemant's tech stack includes ML, SVM, RNN, Deep Learning, NLP, SQL, Naive Bayes, ResNet, XGBoost, Random Forest, Keras, Seaborn, CNN, Scikit, Python, TensorFlow, Pandas, Computer Vision, and Hyperparameter.