Time Series Analysis

Khal Ben

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About this service

Summary

I offer comprehensive Time Series Analysis to help you unlock the full potential of your time-based data. My unique approach combines advanced statistical and machine learning, deep learning models with thorough data preparation and visualization techniques, ensuring accurate insights and forecasts tailored to your specific needs. With a focus on delivering actionable results, I provide custom forecasting models, interactive dashboards, and detailed reports to empower your decision-making.

Process

Step-by-Step Process for Time Series Analysis

Understand Client Needs Discuss the project goals and specific requirements to tailor the analysis.

Data Collection Obtain the time-based data from the client, ensuring it's in a suitable format.

Exploratory Data Analysis (EDA) Analyze the data to identify trends, seasonality, and patterns.

Statistical Modeling Apply traditional models like ARIMA and linear regression to establish baseline forecasts.

Advanced Modeling Utilize state-of-the-art machine learning and deep learning models such as N-BEATS, TSMixer, and TiDE for improved accuracy.

Model Evaluation Compare the performance of all models to select the best one for accurate forecasting.

Deployment Deploy the chosen model using a Streamlit app to visualize results, model performance, and make predictions.

FAQs

What is Time Series Analysis?
Time Series Analysis involves examining time-based data to identify trends, seasonal patterns, and forecast future values. It helps organizations make data-driven decisions.
What kind of data do you need from me?
I need time-based data in a readable format (e.g., CSV, Excel). If your data exists in a database, I can assist in extracting it as well. You should provide any relevant information regarding the data and specific variables of interest.
How long does the analysis take?
The timeline varies based on the complexity of your data and specific requirements, but typically, the analysis can be completed within a few days (from 1 to 15 days).
What models will you use for forecasting?
I utilize a range of models, starting with traditional statistical methods like ARIMA and SARIMA, and advancing to state-of-the-art machine learning models such as N-BEATS and TSMixer...
Will I receive a report?
Yes, you will receive a comprehensive report detailing the analysis process, findings, insights, and actionable recommendations.
How do you ensure model accuracy?
I evaluate model performance using metrics such as Mean Absolute Percentage Error (MAPE), Mean Squared Error (MSE), and Mean Absolute Error (MAE) to select the best-performing model for accurate forecasts.
Can I interact with the results?
Yes! I deploy the final model using a Streamlit app, allowing you to visualize results, track model performance, and make predictions interactively.
Do I need to have technical knowledge to use the results?
No, I provide user-friendly visualizations and reports that make it easy to understand the insights, regardless of your technical background.

What's included

Holistic time series analysis to identify trends, forecast future values, and gain valuable insights from your time series data.
What I Offer 1- Data Preparation: Address missing values, outliers, and inconsistencies to ensure accurate analysis. 2- Exploratory Data Analysis (EDA) Trend Analysis: Detect long-term trends and patterns within your data. Seasonality Detection: Identify periodic fluctuations and seasonal variations. 3- Modeling and Forecasting Statistical Models: Apply ARIMA, SARIMA, and Exponential Smoothing for forecasting. Machine Learning Models: Use techniques like Nhits, Nbeats, LSTM and Prophet for advanced forecasting. Model Evaluation: Validate model accuracy with cross-validation and error metrics. 4- Anomaly Detection Irregularities: Identify and analyze unusual patterns or outliers in your data. Visualization and Reporting Charts and Graphs: Create dynamic visualizations to display trends, forecasts, and anomalies. Reports: Provide a detailed summary of findings, models used, and actionable insights. Deliverables Forecasting Models: Custom models for predicting future values based on your data. Visualization Dashboards: Interactive charts and graphs showing trends and forecasts. Analysis Report: A comprehensive report including methodologies, findings, and insights.

Skills and tools

Data Modelling Analyst

Data Scientist

Data Analyst