Numpytrabajos

Intento instalar py-feat con pip y recibo el mensaje “subprocess-exited-with-error” justo en la fase de descarga de dependencias. Aparentemente es la versión de numpy u otros. Necesito que apliques la corrección para que la instalación finalice sin problemas y el paquete quede listo para importarse en mi entorno. Entregables esperados: • Comandos o ajustes aplicados ( actualizado, flags de pip, o mirrors alternativos). • Guía breve para repetir la instalación en otro equipo. Conozco R bastante, pero no Python. Estoy usando colab, hay una notebook en py-feat.org. Solo ocupo que funcione para aplicarlo.

Trabajo cada día con grandes lotes de datos numéricos y necesito que un script en Python se encargue de todo el proceso de forma automática. El flujo básico sería: recibir los archivos (habitualmente CSV o Excel), de api en tiempo real aplicar transformaciones y cálculos predefinidos con NumPy/Pandas, validar resultados y exportar un reporte limpio listo para su análisis. El código debe: • ejecutarse desde línea de comandos en Windows y Linux; • permitir configurar las rutas de entrada y salida mediante argumentos o archivo .ini; • registrar cada paso en un log para poder depurar incidencias. Acepto recomendaciones sobre la arquitectura (scripts sueltos, módulo o notebook convertible), siempre que...

...procesamiento de video en red y la comunicación con hardware externo. Requisitos Técnicos Clave: Lenguaje: Python 3. Recepción de Video: La aplicación debe recibir un stream de video a través de la red utilizando el protocolo NDI. Se recomienda el uso de librerías eficientes como cyndilib en Python. Procesamiento de Imagen: Se debe usar OpenCV de manera optimizada (aprovechando operaciones con NumPy) para realizar la detección de color en formato HSV a más de 120 FPS. Alto Rendimiento: El código debe estar diseñado para un alto rendimiento. Esto implica el uso de multi-threading o multiprocessing para que la recepción de frames NDI y el procesamiento de imágenes ocurran en hilos separados, evitan...

...para resolver la ecuación en coordenadas esféricas. Generar resultados en forma de gráficas que muestren la evolución de la concentración de la sustancia respecto al tiempo y la posición radial. Documentar brevemente el desarrollo del código, los supuestos aplicados y las conclusiones que se pueden extraer de los resultados obtenidos. --- Requerimientos técnicos: Lenguaje preferido: Python (NumPy, Matplotlib) o Excel con macros/formulación. Experiencia en: Resolución de EDPs por métodos numéricos Modelos de difusión de masa o transferencia de calor Uso de condiciones de frontera de tipo Dirichlet o Neumann Entregables: Código funcional y comentado 2 o más gr&aac...

...para resolver la ecuación en coordenadas esféricas. Generar resultados en forma de gráficas que muestren la evolución de la concentración de la sustancia respecto al tiempo y la posición radial. Documentar brevemente el desarrollo del código, los supuestos aplicados y las conclusiones que se pueden extraer de los resultados obtenidos. --- Requerimientos técnicos: Lenguaje preferido: Python (NumPy, Matplotlib) o Excel con macros/formulación. Experiencia en: Resolución de EDPs por métodos numéricos Modelos de difusión de masa o transferencia de calor Uso de condiciones de frontera de tipo Dirichlet o Neumann Entregables: Código funcional y comentado 2 o más gr&aac...

...para resolver la ecuación en coordenadas esféricas. Generar resultados en forma de gráficas que muestren la evolución de la concentración de la sustancia respecto al tiempo y la posición radial. Documentar brevemente el desarrollo del código, los supuestos aplicados y las conclusiones que se pueden extraer de los resultados obtenidos. --- Requerimientos técnicos: Lenguaje preferido: Python (NumPy, Matplotlib) o Excel con macros/formulación. Experiencia en: Resolución de EDPs por métodos numéricos Modelos de difusión de masa o transferencia de calor Uso de condiciones de frontera de tipo Dirichlet o Neumann Entregables: Código funcional y comentado 2 o más gr&aac...

...para resolver la ecuación en coordenadas esféricas. Generar resultados en forma de gráficas que muestren la evolución de la concentración de la sustancia respecto al tiempo y la posición radial. Documentar brevemente el desarrollo del código, los supuestos aplicados y las conclusiones que se pueden extraer de los resultados obtenidos. --- Requerimientos técnicos: Lenguaje preferido: Python (NumPy, Matplotlib) o Excel con macros/formulación. Experiencia en: Resolución de EDPs por métodos numéricos Modelos de difusión de masa o transferencia de calor Uso de condiciones de frontera de tipo Dirichlet o Neumann Entregables: Código funcional y comentado 2 o más gr&aac...

...para resolver la ecuación en coordenadas esféricas. Generar resultados en forma de gráficas que muestren la evolución de la concentración de la sustancia respecto al tiempo y la posición radial. Documentar brevemente el desarrollo del código, los supuestos aplicados y las conclusiones que se pueden extraer de los resultados obtenidos. --- Requerimientos técnicos: Lenguaje preferido: Python (NumPy, Matplotlib) o Excel con macros/formulación. Experiencia en: Resolución de EDPs por métodos numéricos Modelos de difusión de masa o transferencia de calor Uso de condiciones de frontera de tipo Dirichlet o Neumann Entregables: Código funcional y comentado 2 o más gr&aac...

...servicios con soluciones de inteligencia artificial. Estamos buscando un perfil interesado en colaborar en un proyecto inicial de inteligencia artificial utilizando Python. El proyecto se centra en la predicción basada en datos numéricos y está pensado para explorar el potencial de IA en aplicaciones prácticas. Requisitos: Conocimientos básicos de Python y bibliotecas relacionadas con IA como Pandas, NumPy y Scikit-learn. Familiaridad con el manejo de datos numéricos. Capacidad para explicar conceptos técnicos de manera clara y efectiva. Objetivo del Proyecto: El objetivo es desarrollar un modelo sencillo de IA para predecir ventas utilizando datos numéricos históricos. Esto incluirá la configuración ...

...llegan al panel, fecas de animales, animales muertos sobre el panel, entre otros. Actualmente, ya existe un desarrollo avanzado del cual quien tome el proyecto, deberá levantar, evaluar lo que se encuentra programado y continuar con el desarrollo. Se encuentra confeccionado en Python y las librerías integradas para el análisis de puntos calientes y tratamiento de imágenes son: rasterio skimage numpy pickle pandas psycopg2 torch s3 Objetivos específicos ayudar a verificar el levantamiento del proyecto creando los casos de uso y diagrama de secuencia tanto de cómo operará el script Python tanto como deberá interactuar el sitio web para que pueda entregar los inputs al script Python (imágenes clasificadas) y como deb...

Hemos extraído información histórica de un perfil de Twitter y deseamos analizarla. Esta información está en formato JSON y contiene comentarios y opiniones de usuarios en español principalmente. Alcances del proyecto: ◉ Clas...de la polaridad de los comentarios y su intensidad (%)(Ejm: positivo, negativo, neutro). ◉ Clasificación de los comentarios por motivo (Ejm: Atencion al cliente, Tarjetas, Deudas, Abonos, etc) ◉ Clasificación de las emociones de los comentarios (Ejm: Alegría, enojo, miedo, repulsión, sorpresa, tristeza). Herramientas y algoritmos a utilizar: ◉ Google Colab. ◉ Python (pandas, nltk, tensorflow, numpy, sklearn, keras, etc ) ◉ Word Embeddings en español. ◉ Red Neuronal Recurrente LSTM...

Requerimos un desarrollador de Python con una sólida formación en ciencia de datos, o una persona en ciencia de datos con una sólida formación en Python. La persona contratada para este cargo deberá cumplir con los siguientes criterios: - Fuerte comprensión de los módulos de ciencia de datos de Python como Pandas, NumPy, SciPy, Matplob - Familiarizado con Linux y Docker - Hispanohablantes nativos La persona contratada para este puesto debe ser hispanohablante (sin excepciones, se requieren llamadas diarias con el cliente en español) Este sera un trabajo de tiempo completo (hasta 40 horas por semana) La persona contratada para este puesto debe utilizar el rastreador de tiempo de freenlancer. El desarrollador contratado para ...

Debo completar unas tareas que consisten en pequeños programas de código simple utilizando Python y librerías científicas: numPy, Matplotlib, Pandas y SciPy. Se proporcionará documento con los requisitos exactos, documentos con programas de ejemplo y ejercicios resueltos y plantilla para la resolución. Es imprescindible que se vaya entregando cada pequeño programa a medida que se termine, y la totalidad del proyecto tiene que estar para mañana a las 20:00. Presupuesto de 50€. Gracias

Buenas tardes, necesito para hoy realizar este unico ejercicio, que funcione al pie de la letra Enunciado: En la empresa hay 4 empleados en comisión de servicio. Se requiere controlar el gasto total en la semana para cada uno (Lunes a Viernes) Los empleados se identifican con un código numérico. Matrices: 1.- Empleado: almacena  código del empleado, nombre y cargo de los empleados. 2.- Gastos: almacena  código del empleado, gasto de lunes a viernes separados, gasto de la semana Se pide: a.- Usar funciones para: b.- Menú c.- Ingresar datos en las matrices. Verificar que exista el Empleado antes de ingresar los gastos. d.- Buscar el detalle de los gastos realizados por un determinado empleado; se busca por el código y se...

Sopra selecciona, para importantes proyectos de la Compañía un perfil de PROGRAMADOR SENIOR / ANALISTA PROGRAMADOR PYTHON con al menos 2 años de experiencia en la implantación de modelos matemáticos: Se requiere: - Experiencia en Python (Scikit Learn, Numpy, Scipy y Matplotlib)Se valorará: - Experiencia en Graph Tool o Network X, también R, RBGL y Boost Graph, C++Buscamos profesionales con capacidad de trabajo en equipo, ganas de aprender, mejorar y asumir nuevos retos, iniciativa y responsabilidad en el trabajo Ofrecemos: - Estabilidad laboral.- Acuerdos sociales y beneficios para los empleado: Seguro de vida, Tickets Restaurante, descuento en la contratación de un seguro médico privado opcional con Adeslas. - Crecimi...

Sopra selecciona, para importantes proyectos de la Compañía un perfil de PROGRAMADOR SENIOR / ANALISTA PROGRAMADOR PYTHON con al menos 2 años de experiencia en la implantación de modelos matemáticos: Se requiere: - Experiencia en Python (Scikit Learn, Numpy, Scipy y Matplotlib)Se valorará: - Experiencia en Graph Tool o Network X, también R, RBGL y Boost Graph, C++Buscamos profesionales con capacidad de trabajo en equipo, ganas de aprender, mejorar y asumir nuevos retos, iniciativa y responsabilidad en el trabajo Ofrecemos: - Estabilidad laboral.- Acuerdos sociales y beneficios para los empleado: Seguro de vida, Tickets Restaurante, descuento en la contratación de un seguro médico privado opcional con Adeslas. - Crecimi...

Sopra selecciona, para importantes proyectos de la Compañía un perfil de PROGRAMADOR SENIOR / ANALISTA PROGRAMADOR PYTHON con al menos 2 años de experiencia en la implantación de modelos matemáticos: Se requiere: - Experiencia en Python (Scikit Learn, Numpy, Scipy y Matplotlib)Se valorará: - Experiencia en Graph Tool o Network X, también R, RBGL y Boost Graph, C++Buscamos profesionales con capacidad de trabajo en equipo, ganas de aprender, mejorar y asumir nuevos retos, iniciativa y responsabilidad en el trabajo Ofrecemos: - Estabilidad laboral.- Acuerdos sociales y beneficios para los empleado: Seguro de vida, Tickets Restaurante, descuento en la contratación de un seguro médico privado opcional con Adeslas. - Crecimi...

...Vamos, que tenemos una montada interesante.<br /><br />¿A quién buscamos?<br /><br />A alguien con actitud. Necesitamos a una persona despierta, con ganas de aprender y que quiera aportar.<br />Conocimientos que valoramos (no, no hemos dicho requeridos):<br />- JavaScript<br />- CoffeeScript.<br />- AngularJS.<br />- Python<br />- Django.<br />- Django REST framework.<br />- Machine Learning<br />- numpy / scipy<br />- ntlk<br />- Administración de sistemas / DevOps<br />- Amazon Web Services.<br />- Ansible.<br />- Desarrollo y herramientas ágiles<br />- Scrum.<br />- Git.<br />- Speak English.<br /><br />&ique...

...imagen captcha, Datos de salida: JSON que ponga el código obtenido del captcha Adjunto un código que actualmente tenemos para otro servicio de captcha. #!/usr/bin/env python2.7 # -*- coding: utf-8 -*- import import from import json_encode import urllib2 as urllib from PIL import Image from cStringIO import StringIO import numpy as np import tesserwrap import cv2 import base64 class MainHandler(): def get(self): print "El sistema correra" # Url de búsqueda de imagen url = self.get_query_arguments('url') # Tiene resultados (?) if not len(url): return # Decodificamos el contenido de url _url_decode = (url[0]) # Obtenemos el captcha url = _url_decode

...Data4 Python + Django Web Developers Data4 esta buscando desarrolladores en Django/Python para el departamento de Data Driven Web Platforms. El departamento esta encargado de elaborar complejas plataformas usando Django, PostgreSQL+ PostGIS / Mysql, Memcached, Haystack con Solr, y su integración a Big Data con Hadoop, Hbase, R y las librerías en Python para machine learning como PyBrain, NumPy, SciPY. Trabajamos bajo la metodología ágil SCRUM con mucha apertura a la experimentación y el auto aprendizaje. Nuestros desarrolladores trabajan desde la arquitectura de la base de datos hasta la construcción de excelentes UI y UX de las plataformas. Data4 tiene su base en la Ciudad de México.  Responsabilidades<ul>...

I have a raw data set that I need translated into clear, actionable insights. At this stage I’m flexible on the tools you use—Python (pandas, NumPy, matplotlib), R, Excel, Power BI, or a mix—so long as the findings are easy for a non-technical stakeholder to understand and the work can be reproduced later. Here’s what I’d like to walk away with: • a cleaned, well-structured version of the data (same file type I provide, unless you suggest better) • an executive-level summary that highlights the most important patterns and any anomalies worth attention • the working files—code notebooks, pivot tables, or dashboards—so I can trace every step of the analysis Acceptance criteria: results must reconcile with the source dat...

Math for Data Analytics and Visualizing Distribution 1. Consider the following matrix: Matrix 57 67 35 47 59 62 77 22 24 44 72 21 -What are its dimensions? -Create a numpy array corresponding to this matrix. -Create a numpy array of shape (5,3) and fill it with random integers. 2. Using pandas, -Load the Walmart sales dataset -Select store 1 and plot its weekly sales over time. Make sure to adhere to visualization guidelines in your plot. -Identify trends, peaks, and valleys in the sales. -Modify your plot to also display the occurrence of holidays. 3. Using the Walmart sales data for store 1, you will now create a simple probabilistic model for sales -Create an additional column, named ‘Week Number’ in your dataframe that translates the ‘Date’ t...

...SHAP or LIME so each prediction can be traced back to the contributing EEG channels, scales, or time-windows. • Performance evaluation: deliver detailed metrics (accuracy, sensitivity, specificity, F1, ROC-AUC, false-alarm rate per hour) on a solid cross-validation split and, if possible, an unseen hold-out set. Deliverables must include – Clean, well-commented source code (Python preferred: NumPy, Pandas, MNE, scikit-learn, SHAP/LIME, etc.) – A concise technical report that documents preprocessing choices, feature engineering, modelling decisions, and performance tables/plots – Reproducible experiments packaged in notebooks or scripts with clear run instructions – A read-me explaining environment setup and how to deploy or further train the...

...functions purely under the atr namespace without breaking existing features. The main focus is bug fixing: some functions now throw import errors or mis-route data after the initial adpu removal I attempted. Your task is to clean up those faults, adjust any hard-coded paths or variables, and make sure all unit tests (pytest) pass again. Familiarity with typical data-handling frameworks (pandas, NumPy) is a plus because several utilities rely on them. Deliverables: • Updated Python source files with adpu dependencies fully removed or replaced • Clear commit messages or a change log explaining each fix • Confirmation that the refactored project runs from without errors and all existing tests pass Once the above is complete and verified in my staging env...

...needs a full machine-learning workflow built in Python. The business objective and the kind of data we will work with are still open for discussion, so I’m counting on your expertise to help me refine the goal, pick the right algorithms, and prepare a clean, reproducible pipeline. What matters right now is that everything runs in Python 3.x and relies on well-supported libraries such as pandas, NumPy, scikit-learn, TensorFlow or PyTorch. Once we agree on the exact use-case, you will: • set up data-preprocessing scripts and exploratory notebooks • build, train, and tune the initial model • deliver clear, commented code with a brief report explaining choices, metrics, and next-step recommendations The work is complete when I can run your code on my loc...

...and the key performance metric I care about. What I expect from you: • Exploratory analysis that highlights trends, seasonality, outliers, and any useful lags or engineered features. • A robust regression model suited to time-series behaviour (ARIMA, Prophet, XGBoost, LSTM, or similar—feel free to justify the best choice). • Code written in Python using familiar libraries such as Pandas, NumPy, Scikit-learn (plus statsmodels, TensorFlow, or PyTorch if needed). • Clear evaluation with train/validation splits, back-testing, and accuracy metrics (MAPE, RMSE, or another metric we agree on). • Concise visualisations—matplotlib / seaborn for the notebook and, if helpful, a lightweight Power BI or Jupyter dashboard so stakeholders see how ...

...insight is important, so the notebook or script has to generate intuitive plots—scatter trends, residual diagnostics, whatever best tells the story of model quality and feature impact. After modelling, package the chosen estimator in a lightweight Streamlit app where a user can key in property details and instantly see a predicted price. Deliverables • Clean, well-commented Python code (Pandas, NumPy, scikit-learn, Matplotlib / Seaborn, Streamlit) • A concise report explaining preprocessing steps, feature choices, model comparison results, and recommendations • The Streamlit interface ready to run locally (with instructions) • Any supplementary documentation needed to reproduce the full workflow end to end If something in the data suggests addi...

...tables directly from our warehouse (PostgreSQL access provided) and focus on the feedback text that customers leave after each support interaction. I need that text distilled through frequency analysis—think n-gram counts, keyword frequencies, TF–IDF weights—so the model can learn which recurring themes correlate with attrition. Modelling requirements The pipeline should be written in pandas, NumPy, and scikit-learn, with XGBoost or LightGBM powering the final estimator. Treat class imbalance with SMOTE (or a proven alternative) and surface feature importance with SHAP. If you already log experiments in MLflow, that is a plus and will streamline later iterations. Dashboard Wrap the finished model in a Streamlit app that shows: • an overview KPI pane...

...deployment. 3. Deployment Readiness The final solution should be deployment-ready and include: * Serialized model artifacts (Pickle, Joblib, ONNX, etc.) * Inference scripts or API endpoints * Requirements file and environment setup instructions * Docker containerization (preferred) * Documentation for deployment and maintenance Technical Requirements Preferred Technologies: * Python * Pandas * NumPy * Scikit-learn * XGBoost, LightGBM, or CatBoost * Apache Airflow (optional) * FastAPI or Flask * Docker * PostgreSQL or MySQL Deliverables * Complete ETL pipeline source code * Trained machine learning model * Model evaluation report * Feature engineering documentation * Deployment-ready package * API for prediction (if applicable) * Technical documentation * Installation a...

I need a simple Streamlit dashboard built in Python that loads data from a numpy .npz file and displays investment analysis charts. The dashboard should run locally with streamlit run app.py. What I need: 5 pages using Streamlit multi-page routing. Each page shows metrics and 2-3 Plotly charts for a different asset. The charts are: IRR probability distribution (histogram/KDE), DSCR by year (bar chart), and a scenario comparison (horizontal bar chart). One sidebar with a scenario dropdown that updates the charts. Tech stack: Python, Streamlit, Plotly, numpy. No database, no authentication, no deployment needed. Desktop only. Data: I will provide a .npz file with pre-computed numpy arrays (IRR distributions, DSCR arrays, scenario values). I will give you the exact key na...

I have an options-based trading idea that I’d like translated into a fully automated algorithm in Python ...module set) ready to run on a VPS. • A simple config file so I can adjust indicator parameters, option strike selection rules, quantity, and risk settings without touching the code. • Quick back-test or paper-trade demonstration that proves the logic fires correctly. • README explaining setup, required Python libraries, and how to obtain SmartAPI credentials. If you already work with pandas, NumPy, TA-Lib (or any indicator library you trust) and have previous Angel One SmartAPI experience, you’ll get up to speed quickly. Accuracy, clear documentation, and stable execution matter more to me than fancy dashboards, so keep the interface minimal a...

I have a set of raw financial data that I need cleaned, explored, and transformed into clear trend insights. The job is squarely in the Data Analysis space, and Python is the language I want everything built in. Here is what I’m after: • Import and tidy the financial data (...narrative summary of your findings. I’ll consider the work complete when I receive: 1. Well-commented Python scripts or Jupyter Notebook that reproduces the analysis end-to-end. 2. The generated charts in PNG or embedded in the notebook. 3. A short written brief (PDF or Markdown) explaining the key trends uncovered and how you arrived at them. If you’re comfortable working with Pandas, NumPy, statsmodels, or similar toolkits and can turn around clear, reproducible insight...

...beginner-level programmers, just 1–5 people) over the next three months. The goal is simple: take us from “zero” to genuinely confident in day-to-day coding so we can handle our own projects without supervision. The curriculum needs to balance theory with plenty of hands-on practice. We want to concentrate on three pillars: • Data analysis – cleaning, manipulating, and visualising data with Pandas, NumPy, and Matplotlib/Seaborn. • Web development – building lightweight web apps and APIs using Flask or Django. • Automation & scripting – writing robust scripts to automate routine tasks, from file handling to simple DevOps-style chores. I need someone who can: • Design a clear week-by-week roadmap, including learnin...

I am looking for someone who understands: Python / Pandas / NumPy Financial time series Macro indicators Backtesting Portfolio performance metrics Optimization methods such as grid search, random search, or Optuna Walk-forward testing / avoiding overfitting Questions for Applicants Please answer: Have you built any Python financial backtest or quant research notebook before? Have you worked with FRED or macroeconomic data? How would you test different weights without overfitting? What Python libraries would you use? Can you share a relevant example of your previous work?

...and the key performance metric I care about. What I expect from you: • Exploratory analysis that highlights trends, seasonality, outliers, and any useful lags or engineered features. • A robust regression model suited to time-series behaviour (ARIMA, Prophet, XGBoost, LSTM, or similar—feel free to justify the best choice). • Code written in Python using familiar libraries such as Pandas, NumPy, Scikit-learn (plus statsmodels, TensorFlow, or PyTorch if needed). • Clear evaluation with train/validation splits, back-testing, and accuracy metrics (MAPE, RMSE, or another metric we agree on). • Concise visualisations—matplotlib / seaborn for the notebook and, if helpful, a lightweight Power BI or Jupyter dashboard so stakeholders see how ...

...supervise performance in real time • Run historical backtests on minute-level data to validate tweaks before they go live, outputting metrics like win rate, drawdown, and expectancy I value readable, modular code (separate data, logic, execution, and reporting layers) and clear in-line comments so I can extend the system later. Preference for standard libraries plus proven packages such as pandas, numpy, TA-Lib (if helpful), and FastAPI or Streamlit for the monitoring front end—though I’m open to your suggestions. Deliverables will be: 1. Fully commented Python source files and 2. A backtesting notebook or script with sample results 3. Setup instructions to run everything on my local machine or a VPS 4. A brief hand-off session (video or chat) to wal...

...is to take these raw tables all the way from initial cleaning through to a succinct set of findings, visualisations and recommendations that I can present to non-technical stakeholders. The workflow I expect is straightforward: import the files, tidy up missing or inconsistent values, run the exploratory statistics that uncover patterns or anomalies, then build concise plots (Python / pandas / NumPy / Matplotlib or similar) so the story of the data is obvious at a glance. If meaningful, a simple predictive model or correlation analysis would be welcome as well, but only if it genuinely adds value. Deliverables • A reproducible notebook or script with clear comments • All generated charts saved as high-resolution images • A short summary document (one to two...

...SQL servers are involved. Core workflow 1. User selects or drops the CSV/XLSX files. 2. The program performs descriptive statistics (mean, median, variance, standard deviation), correlation matrices, and any other common tests you recommend. 3. Results are exported to a new Excel sheet, PDF, or JSON summary—whatever is simplest to reuse. Tech stack is your call, but Python (pandas, NumPy, SciPy) or a lightweight C#/.NET implementation would suit the environment here. The code must be: • Fully commented and modular so additional metrics can be plugged in later. • Delivered with a brief README and a sample run on the test data I’ll supply. • Free of hard-coded paths so it works cross-platform. Acceptance criteria • Source code ...

...retention playbooks generating customer-specific intervention plans, loyalty programs, discount strategies, and engagement campaigns. • Experienced in Machine Learning, Deep Learning, Artificial Neural Networks, Generative AI, FastAPI, TensorFlow, Streamlit, Data Analytics, and Business Intelligence Solutions. • Skilled in Python, TensorFlow, Scikit-Learn, FastAPI, Streamlit, Plotly, Pandas, NumPy, Machine Learning Pipelines, API Development, and Full-Stack AI Application Development....

...step in and help me run specific analyses, prepare clear summaries, and visualize key findings when deadlines pile up. Here’s what I typically need: • Clean and structure raw financial data so it is ready for analysis (Excel, CSV, SQL exports). • Perform descriptive and comparative analyses—trend, variance, ratio, or other finance-focused techniques—using tools such as Excel, Python (pandas, NumPy), or R. • Turn results into concise written insights and, when useful, simple charts or dashboards that I can drop straight into client presentations. What I care about most is proven experience. In your application, please highlight relevant projects where you worked with financial datasets, the tools you used, and any measurable outcomes you ac...

...early stages of launching a new enterprise and I have a sizeable set of financial data that needs a fresh pair of eyes. The objective is straightforward: dig deep into the numbers, spot hidden patterns I can act on, and highlight anything unusual that could influence my next strategic move. You’ll receive raw transaction tables along with a brief on the business model. Using Python (think pandas, NumPy, maybe a touch of scikit-learn for exploratory modelling) and solid SQL querying, I’d like you to clean the data, explore relationships, and surface any trends or anomalies that aren’t obvious at first glance. Clear commentary in well-structured Jupyter notebooks or a similar environment is preferred so I can follow the logic step by step. By the end, I need: &b...

Python Tutor Needed I'm looking for an experienced Python tutor for one-on-one online training. My budget is $50 for the initial training package. Please let me know: Your Python experience and teaching background The Python version you teach (preferably Python 3.12/3.13) Whether you cover: OOP, file handling, exceptions, modules, packages NumPy and Pandas APIs and web scraping SQL databases Git and GitHub FastAPI, Flask, or Django AI/LLMs, OpenAI APIs, and LangChain Testing, debugging, and virtual environments I am interested in practical learning with real-world projects such as: Automation scripts Data analysis projects Web APIs AI chatbot applications Please include: Course outline/syllabus Number of training hours Teaching format (live online sessions needed) Your a...

...independently execute mid-level data engineering tasks with ownership of projects. Ability to implement Data Warehouse modeling techniques to capture complex business requirements. Ability to contribute to the development of scalable data solutions and streamline reporting. Strong proficiency in SQL, specifically with MS SQL Server 2012 and higher, and Python and libraries like Pandas, PyODBC, NumPy, is required. Experience with BI tools (Power BI) and data visualization. Experience using Fabric, dbt, Dagster or Airflow is highly desirable. Strong analytical and problem-solving skills. Experience with BI/DW lifecycle including source data analysis, ETL, data-marts, reporting, dashboards and analytics. Strong verbal/written communication and data presentation skills, including an ...

I have several raw financial data sets—daily price feeds, transaction logs, and balance-sheet snapshots—sitting in CSV format. The task is to load these files into Python (think pandas and NumPy), clean and merge them where necessary, then dig into the numbers to pinpoint meaningful trends. I need clear, reproducible insight rather than black-box output, so please organise the work in a Jupyter Notebook that: • shows each transformation step, • highlights any assumptions or filters applied, and • concludes with well-labelled visualisations (matplotlib or seaborn are fine) that make the identified trends obvious at a glance. A short written summary of the findings—key upward or downward movements, cyclical patterns, and anything unusual wo...

I'm seeking an experienced Python developer specializing in data analysis for financial data backtesting. Key Requirements: - Proficiency in Python - Strong background in financial data - Expertise in backtesting algorithms and strategies Ideal Skills: - Experience with libraries such as Pandas, NumPy, and Matplotlib - Knowledge of financial markets and instruments - Ability to create efficient and accurate backtesting models Please provide examples of previous work in financial data analysis and backtesting.

...instantly once the model produces a signal, including smart order routing where available. • Risk management controls that cap position size, enforce max daily loss, set dynamic stop-loss and take-profit levels, and pause trading if volatility spikes beyond a preset threshold. I am comfortable with Python, so please build the pipeline in that language and leverage proven libraries such as Pandas, NumPy, scikit-learn or TensorFlow for the modelling layer. The finished app should run on my own server, expose a simple dashboard or CLI for parameter tuning, and log every trade for later analysis. Deliverables: 1. Clean, well-commented source code with installation instructions 2. Back-test report covering at least one year of minute-level stock data 3. Live trading mod...

...straightforward: feed clean historical price data into the model, reproduce every trade exactly as defined, and then report how it would have performed over multiple market cycles. You will receive: • The full set of entry, exit and position-sizing rules in plain language. • A link to the historical price files I already maintain. What I need from you: • Well-structured code (Python with Pandas/NumPy, or another language you prefer) that replicates the rules accurately. • Clear performance statistics—total and annualised return, max drawdown, Sharpe and win-rate. • An equity-curve chart plus a concise summary explaining whether the strategy passes a basic viability test. Acceptance criteria 1. Results are fully reproducible on my side b...

A small, beginner-level Python script is partly written and I need it brought to the finish line quickly. The goal is simple: make the code work flawlessly, keep it clean and readable, and walk me through how every part works so I fully understand it. The script currently relies only on core Python—no external libraries such as Pandas, NumPy, Requests, or BeautifulSoup are planned—so please keep the solution in standard Python 3. I may have introduced a few syntax or logic hiccups along the way; if any runtime surprises pop up, squash those as well. What I expect from you: • A completed, well-structured .py file that runs without errors. • Clear inline comments plus a concise explanation document (or markdown file) outlining the flow, key functions, and a...

...dashboard. Key Deliverables & Technical Milestones: Automation & Ingestion (Unix & Shell Scripting): * Developed production-grade Unix Shell scripts to automate daily data downloads from remote servers. Implemented error handling, logging, and file validation checks within the shell pipeline to ensure zero data loss during ingestion. Data Cleaning & Preprocessing (Python): * Utilized Python (Pandas/NumPy) to handle raw, messy source data. Resolved structural data issues, treated missing values, eliminated duplicates, and standardized data formats for downstream consumption. Scalable ETL Processing (PySpark): * Leveraged PySpark to process and transform large-scale datasets efficiently, optimizing partition strategies to reduce execution time. Executed complex busi...

This project revolves around designing and coding a bespoke Python algorithm from the ground up. The exact domain—data analysis, machine learning, automation, or another algorithmic niche—will be defined together after an initial scoping call, so broad knowledge of Python’s scientific and data-handling ecosystem (NumPy, pandas, scikit-learn, etc.) is valuable. Input data is still flexible; guidance on sourcing, cleaning, or even synthetically generating the right datasets is part of the brief. What matters most is an efficient, well-structured solution that is easy to maintain, extend, and benchmark. Clear inline comments and concise documentation are non-negotiable so that future iterations remain straightforward. Deliverables • Fully functional Pytho...