Predictive modelling and machine learning by Himanshu NarwalPredictive modelling and machine learning by Himanshu Narwal
Predictive modelling and machine learningHimanshu Narwal
Cover image for Predictive modelling and machine learning
Building and deploying predictive models using machine learning algorithms.

What's included

Data preparation and cleaning
Preparing and cleaning the dataset for analysis and modelling.
Exploratory data analysis (EDA)
Analysis to understand the data distribution, relationships, and key patterns.
Feature engineering
Creating and selecting features to improve model performance.
Model development
Developing and training machine learning models.
Model evaluation
Evaluating the performance of the machine learning model.
Model tuning and optimisation
Fine-tuning the model to improve its performance.
Model deployment
Deploying the model for use in a production environment.
Model documentation
Comprehensive documentation of the entire modelling process.
Prediction results
Predictions made by the model on new data.
Consultation and support
Ongoing support and consultation to ensure successful implementation and use of the model.
Contact for pricing
Tags
Matplotlib
pandas
Python
scikit-learn
SQL
Data Analyst
Data Scientist
ML Engineer
Service provided by
Himanshu Narwal Delhi, India
1
Followers
Predictive modelling and machine learningHimanshu Narwal
Contact for pricing
Tags
Matplotlib
pandas
Python
scikit-learn
SQL
Data Analyst
Data Scientist
ML Engineer
Cover image for Predictive modelling and machine learning
Building and deploying predictive models using machine learning algorithms.

What's included

Data preparation and cleaning
Preparing and cleaning the dataset for analysis and modelling.
Exploratory data analysis (EDA)
Analysis to understand the data distribution, relationships, and key patterns.
Feature engineering
Creating and selecting features to improve model performance.
Model development
Developing and training machine learning models.
Model evaluation
Evaluating the performance of the machine learning model.
Model tuning and optimisation
Fine-tuning the model to improve its performance.
Model deployment
Deploying the model for use in a production environment.
Model documentation
Comprehensive documentation of the entire modelling process.
Prediction results
Predictions made by the model on new data.
Consultation and support
Ongoing support and consultation to ensure successful implementation and use of the model.
Contact for pricing