Description
Machine Learning and Applications Training with Python is a 3-day live online or in-person program for software developers, data analysts, and engineers with basic Python programming knowledge. It covers machine learning concepts together with the process of developing and evaluating models in Python.
The curriculum ranges from types of learning, data pre-processing, feature extraction, and evaluation metrics to the use of Scikit-Learn. Regression, classification, clustering, and boosting models are covered under the headings of theory, model, and prediction. You can review the program scope and request a training plan and quote for your organization’s team.
Outline
Machine Learning Fundamentals
What Is Machine Learning?
Real-Life Examples
Basic Concepts and Terminology
Types of Learning
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
Data Pre-Processing
- Data Cleansing
- Data Transformation
- Data Reduction
Feature Extraction
Machine Learning Model Evaluation Methods
- Confusion Matrix
- Accuracy, Recall, Precision
- R2 Score
- F1 Score
- AUC-ROC Curve
- Mean Absolute Error (MAE)
- Mean Squared Error (MSE)
Tools for Performing Machine Learning with Python
- Scikit-Learn Module and Machine Learning
Machine Learning Algorithms/Models and Application Development
- Regression Models (Theory, Model, Prediction)
- Simple Linear
- Multiple Linear
- Classification Models (Theory, Model, Prediction)
- Classification with Decision Trees
- Classification with Support Vector Machines (SVM)
- Clustering Models (Theory, Model, Prediction)
- Clustering with the K-Means Algorithm
- Determining the Optimal Number of Clusters with the Elbow Method
- Clustering with the K-Means Algorithm
- Boosting (Prediction) Models (Theory, Model, Prediction)
- Gradient Boosting
- XBoost
- LightGBM
Prerequisites
A basic knowledge of Python programming.
Related Training and Quote
To focus on multi-layer neural networks, see the Deep Learning and Applications with Python Training; for big data processing coverage, see the Big Data and Applications with Python Training programs.
To get a training plan and price quote for your organization, you can fill out the Contact Form on this page. For other ways to reach us, you can use the BlueMark Academy contact page.
Frequently Asked Questions
How Long Is the Machine Learning with Python Training?
The program lasts 3 days.
Is the Training Online?
The training format is live online or in person.
What Are the Prerequisites?
Participants need a basic knowledge of Python programming.
Which Types of Models Are Covered?
Regression, classification, clustering, and boosting models are covered under the headings of theory, model, and prediction.
Are Scikit-Learn and Model Evaluation Covered?
Yes. Along with the Scikit-Learn module, the curriculum includes evaluation metrics such as the Confusion Matrix, R2, F1, AUC-ROC, MAE, and MSE.
How Can I Request a Quote for Corporate Training?
You can submit your organization’s training needs through the Contact Form on this page and request a training plan and price quote.