6 of 6 NumPy Jobs in Scotland

applied experience building production Python systems, including web/API services (Flask or FastAPI) and the ML/NLP ecosystem (scikit-learn, pandas, NumPy, spaCy, PyTorch or TensorFlow). Demonstrated experience taking machine learning models from prototype to production - training, packaging, deployment, monitoring, retraining, and decommissioning - in real-world business ...

your Python skills by building a car price prediction app using Python and Streamlit. Step 6 – Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 – AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using ...

applied experience building production Python systems, including web/API services (Flask or FastAPI) and the ML/NLP ecosystem (scikit-learn, pandas, NumPy).Demonstrated experience taking machine learning models from prototype to production - training, packaging, deployment, monitoring, retraining, and decommissioning - in real-world business applications.Experience with building LLM/ ...

algorithms for efficient data processing and model optimization Error handling and debugging using try-catch blocks, logging, and debugging tools Data Processing: Pandas and NumPy for data manipulation, cleaning, and numerical operations SQLAlchemy or psycopg2 for database connectivity and ORM operations Boto3 for AWS service integration and automation AWS (working ...

context and memory management, and interoperability protocols such as MCPExperience with machine learning frameworks and data science packages such as PyTorch, TensorFlow, scikit-learn, NumPy, pandas, SciPy, and statsmodelsExperience deploying to AWS, including services such as SageMaker and Bedrock, and operating production large language model and machine learning workloads with ...

machine learning engineering roles Strong, demonstrable experience with machine learning for classification tasks Proficiency in Python and relevant libraries: scikit-learn, TensorFlow, pandas, NumPy Real-world experience working with sensor data, time-series data, or IoT data streams Familiarity with embedded ML tools and approaches: TensorFlow Lite, Edge Impulse, ONNX ...