I will build time series forecasting models in python

China

I speak English, Chinese

Data Analyst Big Data Statistical Analysis Machine Learning

I am an Applied Statistics graduate student with a strong foundation in statistical modeling, machine learning, and structured data analysis. I am proficient in Python and tools like scikit-learn and ...

About this Gig

Time series data contains trends, seasonality, and uncertainty that ordinary models may miss. I will analyze and forecast your data in Python, selecting methods that match its structure instead of forcing one model.

Suitable uses include sales, demand, inventory, web traffic, energy, operations, and sensor data.

My workflow can include:

Date frequency and missing-timestamp checks

Trend and seasonality analysis

Preprocessing and outlier review

ARIMA, SARIMA, exponential smoothing, Prophet, or machine learning models

Time-aware validation with MAE, RMSE, or MAPE

Forecast plots and prediction intervals when supported

Depending on your package, you may receive a baseline forecast, model comparison, tuning, reusable Python code, and a detailed report.

I am a graduate student in Applied Statistics with experience in statistical modeling and machine learning. I provide honest error evaluation and do not guarantee a predetermined accuracy.

Please provide a date or time column and a numeric target. Message me before ordering for multiple series, external variables, or unusual data structures.

build time series forecasting models in python

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build time series forecasting models in python

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build time series forecasting models in python

build time series forecasting models in python

build time series forecasting models in python

Expertise:

Decision trees

•

Anomaly detection

•

Predictive analysis

Programming language:

Python

•

R

•

MATLAB

•

SQL

•

Java

Frameworks:

PyTorch

•

Panda

Tools:

Jupyter Notebook

•

Excel

•

MLflow

•

Amazon SageMaker

My Portfolio

Other Data Science & ML Services I Offer

Machine Learning
Starting at $90

FAQ

Question: What data do you need to start?

Answer: Please provide a dataset with a date or time column, a numeric target, the desired forecast horizon, the data frequency, and a brief explanation of the business goal.

Question: How much historical data is required?

Answer: There is no universal minimum. Enough history to observe trend and seasonal cycles is preferred. Please send a sample before ordering if you are unsure.

Question: Which forecasting model will you use?

Answer: I select models based on the data structure, frequency, trend, and seasonality. Methods may include ARIMA, SARIMA, exponential smoothing, Prophet, or machine learning models.

Question: Can you guarantee a specific forecasting accuracy?

Answer: No responsible forecast can guarantee future accuracy. I use time-aware validation and suitable error metrics to provide an honest assessment of model performance.

Question: Can you forecast multiple products, locations, or target series?

Answer: Each package covers one target series unless otherwise agreed. Select the Additional Time Series extra or message me for a custom offer involving multiple series.

Question: Will I receive the Python code and a report?

Answer: Basic includes the forecast and plots. Standard includes reusable Python code and model comparison. Premium includes the code, advanced analysis, and a detailed report.

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