Machine Learning Applications: Design and development of AI solutions, building and training of learning models for specific use-cases.
⚙️ Generative AI through prompt design and engineering, aligning and constructing instructs for machines to interact with models for automated content creation and analysis.
- Object detection, image segmentation and image generation: Text-to-image, Image-to-image, Inpainting 🖼️ , Upscaling
- Text-to-music generation 🎶
- Data preparation and model fine-tuning 👩💻
- Sentiment analysis, summarization, classification, extraction and ideation for text 🪄
📊 Data Analytics powered by Python and AI
📈 Research & Strategy: Providing research and guidance on AI adoption and strategy development
🔍 Supervised Machine Learning: Regression and Classification techniques.
🔄 Unsupervised Learning: Clustering, Anomaly Detection, Collaborative & Content-Based Filtering techniques.
🧠 Advanced Learning Algorithms: Neural Networks and Decision Trees.
Certifications
Stanford University & DeepLearning.AI: Machine Learning Specialization
2 month program. Completed November 2023
Credential
- Supervised Machine Learning: Regression and Classification
- Advanced Learning Algorithms
- Unsupervised Learning, Recommenders, Reinforcement Learning
DeepLearning.AI: TensorFlow Developer Professional Certificate
2 month program. Completed July 2021
Credential
- Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
- Convolutional Neural Networks in TensorFlow
- Natural Language Processing in TensorFlow
- Sequences, Time Series and Prediction
MITx XSeries Program: Computacional Thinking using Python
5 month program. Completed June 2020
Credential
- 6.00.1x: Introduction to Computer Science and Programming Using Python, Mar 2020
- 6.00.2x: Introduction to Computational Thinking and Data Science, Jun 2020
