About

Deekshith B D is a highly skilled Jr. Software Developer with a focus on Data Science. With a strong background in mathematics, statistics, probability, calculus, and linear algebra, he has a keen interest in contributing to team success through hard work. Deekshith has 1.36 years of relevant experience in the field of Data Science, Machine learning, and Tableau. He is well-versed in various machine learning algorithms, such as Simple Linear Regression, Multiple Regression, Polynomial Regression, Logistic Regression, SVM, KNN, Naive Bayes, Decision Tree, Random Forest, AdaBoost, Gradient Boosting, XGBoost, K-fold cross-validation, Grid Search, and Random Search. Deekshith has experience in minimizing the cost function based algorithms like Gradient Descent, Stochastic Gradient Descent, and Batch Gradient Descent and Regularizing Linear Models with the help of Ridge, Lasso, and Elastic Net. Deekshith is skilled in clustering algorithms like K means, Agglomerative Hierarchical Clustering, Divisive Hierarchical Clustering, DBScan, Association Rule learning, and Dimensionality Reduction like PCA, LDA. He has hands-on experience in feature engineering with Python, missing value treatment, outlier handling, data transformation, feature selection, and reshaping data using Python packages like NumPy, Pandas, and Scikit Learn. Deekshith is proficient in data visualization techniques with the help of Matplotlib, Seaborn, and Tableau. He has good knowledge of Deep Learning (DL) and hands-on experience with Neural Network Architecture, Loss Function, Cost Function, Optimizers, Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Recurrent Neural Networks (RNN), LSTM. Deekshith is skilled in libraries like NumPy, Pandas, Matplotlib, Seaborn, Scikit Learn, TensorFlow, Keras, OpenCV, and NLTK. He has a basic understanding of Computer Vision techniques like Image pre-processing, Image Segmentation, Object detection, Object recognition, Object tracking, and Natural Language Processing (NLP) techniques. Deekshith has worked on real-life use cases of Face detection and matching technology using advanced Deep learning concepts. He is a self-motivated team player with good communication and presentation skills. Deekshith has completed his Bachelor of Engineering from Visvesvaraya Technological University and is currently pursuing a