NumPy Jobs

I have a CSV that logs product sales alongside TV, Radio, and Newspaper advertising spend. I want a clean, reproducible Python workflow that turns this data into an accurate sales-forecasting model and a concise set of insights for decision-makers. The raw file contains a few gaps, so your first step is to inspect, clean, and appropriately impute missing values. Once the data is tidy, explore it with Pandas, NumPy, Matplotlib, and Seaborn to surface correlations and outliers. For modelling, start with a well-documented Linear Regression approach using scikit-learn. If you see a clear uplift from adding regularisation or polynomial terms, feel free to include that comparison, but keep the final deliverable focused on a model that is simple to interpret and easy to retrain. Deliverables ...

I have fallen several days behind on a set of Python-based programming and machine-learning assignments that live in Google Colab (links below). The notebooks already include starter code and task prompts, but a number of cells remain unfinished or are throwing errors. I need someone who can step in quickly, finish the required functions, debug the failing sections, and make sure each notebook runs top-to-bottom without issues. Google Colab notebooks 1. 2. 3. What’s involved • Programming assignments: implementing missing Python functions, cleaning up logic, ensuring correct output formatting. • Machine-learning assignments: completing model training/evaluation sections (likely scikit-learn, pandas, NumPy), fixing runtime or shape errors, and confirming metric...

I’m sitting on several datasets—a mix of tidy spreadsheets and raw text logs—and I need them transformed into business-ready insights with reliable predictive power. Your first task will be to clean and consolidate this structured and unstructured data in Python using Pandas / NumPy and, where helpful, SQL queries. Once the data pipelines are solid, I’d like an exploratory analysis that highlights key patterns or anomalies before we move into supervised models that forecast the metrics I care about most. For visual communication, every important finding should flow into an interactive Power BI dashboard. I lean on these dashboards to brief non-technical stakeholders, so clarity and drill-down capability matter as much as aesthetic polish. Deliverables • Cle...

I have completed a laboratory experiment and gathered the raw data; what I now need is a polished lab report that drills straight into the results section, with an explicit, quantitatively-driven error analysis. The procedure and hypothesis portions are already documented elsewhere, so the bulk of the narrative should concentrate on how experimental uncertainty arose, how it propagated through the calculations, and how it ultimately affects the reliability of the conclusions. You will receive: • the original data tables (instrument readings, calibration sheets, and environmental notes) • my preliminary calculations in spreadsheet form • a brief outline of the experiment’s objective and method for context What I expect back: • a concise yet rigorous rep...

Headline: Computational Chemist & Molecular Modeller | Computer-Aided Drug Design (CADD) Expert I provide high-precision in-silico drug discovery services, leveraging a deep technical stack that ranges from rapid virtual screening to high-level quantum mechanical calculations. With a focus on generating publishable, wet-lab-ready data, I bridge the gap between theoretical modeling and experimental validation. Technical Expertise & Workflow: • Structure Preparation & Optimization: Advanced protein/ligand preparation using Avogadro and UCSF Chimera/PyMOL. • Virtual Screening & Docking: High-throughput screening using PyRx and AutoDock Vina, including flexible docking and covalent docking protocols. • Quantum Chemistry (QM): Precision electronic structure calcul...