Predictive Modeling with Machine Learning using Python

Duration: Hours



    Training Mode: Online



    In this section, we’ll delve into the fundamentals of predictive modeling with machine learning, focusing specifically on techniques implemented in Python.

    We’ll explore various aspects of building predictive models, from data preprocessing to model evaluation, leveraging the powerful libraries available in the Python ecosystem.

    Through practical examples and step-by-step guidance, you’ll gain a solid understanding of how to apply machine learning algorithms to real-world datasets for predictive analysis. Let’s embark on this journey into the realm of predictive modeling with Python!


    1 . Introduction to Predictive Modeling

    Overview of Predictive Modeling
    Importance and Applications
    Fundamentals of Machine Learning
    Python Setup and Environment

    2 . Data Preprocessing

    Data Cleaning
    Handling Missing Values
    Feature Scaling
    Handling Categorical Data
    Data Transformation and Encoding

    3 . Exploratory Data Analysis (EDA)

    Descriptive Statistics
    Data Visualization in Machine Learning using Python
    Correlation Analysis
    Feature Importance

    5 . Supervised Learning Algorithms

    Linear Regression
    Decision Trees
    Random Forest
    Support Vector Machines
    k-Nearest Neighbors
    Gradient Boosting

    6 . Model Evaluation and Validation

    Training and Testing Data Split
    Performance Metrics (e.g., accuracy, precision, recall, F1-score)
    ROC-AUC Curve

    7 . Hyperparameter Tuning

    Grid Search in Machine Learning using Python
    Random Search
    Optimizing Model Parameters

    8 . Feature Selection and Engineering

    Importance of Feature Selection
    Feature Importance Techniques
    Creating New Features

    9 . Unsupervised Learning

    Clustering (e.g., K-Means, Hierarchical)
    Dimensionality Reduction (e.g., PCA)

    10 . Time Series Forecasting

    Introduction to Time Series Data
    ARIMA Models in Machine Learning using Python
    Seasonal Decomposition
    Forecasting Techniques

    11 . Model Deployment

    Saving and Loading Models
    Web-based Model Deployment
    Model Monitoring and Maintenance

    Please Visit python Official Site: || Locus Academy has more than a decade experience in delivering the training/staffing onĀ  Predictive Modeling with Machine Learning using Python for corporates across the globe. The participants for the training/staffing on Predictive ModelingĀ  are extremely satisfied and are able to implement in their on going projects.

    Other useful references




    There are no reviews yet.

    Be the first to review “Predictive Modeling with Machine Learning using Python”

    Your email address will not be published. Required fields are marked *