Gurpreet Kaur's Linkedin Analytics

👩🏻‍🎓 Data Scientist || Generative AI Researcher || MLOps || LLMOps|| Data Science || Machine Learning|| NLP || LLMs || DL || CV || Python || SQL || Azure || AWS || Scholar || Hackathon Winner|| Open Source Contributor || Technical Content Writer || Thought Leader 🎯 In my 2+ Overall Diverse Professional Experience in different roles, I've dealt with Data Analytics, Financial Analytics, Security Analytics, Statistical Analysis, Data Visualization, Data Mining, Problem Solving, Decision-Making & Planning, Software Quality Assurance, Information Technology, Information Security, Data Security, Research & Development (R&D). 🎯Adept at Performing Deep dive to Gain Actionable Insights with Excellent Data Analytical Skills, proficient Decision-making capabilities & Problem-solving skills ★ 𝐂𝐨𝐦𝐩𝐞𝐭𝐞𝐧𝐜𝐢𝐞𝐬: Artificial Intelligence| Data Science| Machine Learning| Data Analysis| Deep Learning| Natural Language Processing| Computer Vision| Data Mining| Data Processing| Data Visualization| Data Modeling| Predictive Modelling| Statistics| Text Analytics| Prompt Engineering| Optimization| Hypothesis Testing| Python| Azure| AWS| LLM| MLOps| LLMOps| Explainable AI| Generative AI| Debugging| Deployment ★ 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠: Python, R, Data Mining, Data Processing, Modeling, Data Visualization:Tableau ★ 𝐁𝐢𝐠 𝐃𝐚𝐭𝐚 𝐓𝐨𝐨𝐥𝐬: Microsoft Azure Certified, AWS ★ 𝐌𝐋: Supervised- Unsupervised Learning, Linear - Logistic Regression, Random Forest, Clustering, Feature Engineering, PCA, Bagging, Boosting , Model Selection, Time Series Forecasting ★ 𝐃𝐋: Neural Networks, RNN, LSTM, GRU, CNN, Back Propagation, Transfer Learning, Optimization of Algorithm, Regularization, Hyperparameter Tuning, Batch Normalization ✓ Object Detection Algorithm : YOLOv5, SSD, RetinaNet, R-CNN, Faster RCNN, Efficient Det ✓ Semantic Segmentation Algorithms: Unet, FCN, SegNet, DeepLab, DeepLabv3 , Unet++ ✓ Generative Adversial Networks ✓ Instance Segmentation, Vision Transformer, Autoencoder, Capsule Net, RBF, Deep Belief Network, Variance Auto Encoder, Wavelet CNN, etc ★ 𝐍𝐋𝐏 Tokenization, Stemming and Lemmatization, POS Tagging, NER,, Sentiment Analysis, Topic Modeling, Text Classification, Word Embeddings, Seq2Seq Models, Attention Mechanisms and Transformers, Language Modeling. • Frameworks: NLTK, Spacy, Gensim, Hugging Face's Transformers, torchtext, Stanford CoreNLP, Langchain • Prompt Engineering, LLM’s, LLMOps with MLflow ★ 𝐒𝐨𝐟𝐭 𝐒𝐤𝐢𝐥𝐥𝐬: Mentorship, Leadership Development, Team Player, Communication Skills, Storytelling, Critical Thinking.