Results-driven self-taught Machine Learning Engineer specializing in Deep Learning, with a focus on Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs). Proficient in traditional machine learning frameworks and experienced in MLOps practices. Passionate about developing innovative solutions, I have successfully applied CNNs and RNNs to solve complex problems in domains such as computer vision and natural language processing using frameworks such as TensorFlow (Keras API) and PyTorch. Additionally, I possess a solid understanding of traditional machine learning algorithms (SVMs, KNN, Gradient Boosting techniques, PCA), feature engineering, and data preprocessing techniques, enabling me to effectively tackle diverse problem domains. I have actively engaged with platforms such as Kaggle and PapersWithCode to enhance my skills and stay at the forefront of the field. Have included latest advancements in the field such as use of ChatGPT in my workflow.