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Hands-on Predictive Analytics with Python
Description
Hands-on Predicitive Analytics with Python Introduction
Dive into the world of data-driven forecasting with our “Hands-on Predictive Analytics with Python” course. Over three intensive days, you’ll uncover the secrets of predictive analytics, learning how to harness Python’s extensive libraries to transform raw data into actionable insights. This course is meticulously structured to take you from the basics of data handling to the complexities of model deployment, ensuring a comprehensive understanding of the field.
Starting with the essentials of Python for data science, participants will engage in real-world exercises that cover every step of the predictive analytics process, including data cleaning, exploration, and visualization. You’ll experiment with advanced modeling techniques using Python’s top tools like NumPy, Pandas, and Matplotlib, and dive into sophisticated algorithms that power today’s AI—K-Nearest Neighbors, Random Forests, and neural networks. With practical examples and direct coding practice, you’ll gain the proficiency needed to build, tune, and deploy predictive models effectively.
This course promises not just to educate but to empower, offering you the skills and knowledge to leverage predictive analytics in Python proficiently in any professional setting. By the end of the sessions, you will have a solid foundation in the principles of predictive analytics and the practical capabilities to apply these techniques in your own projects.
Hands-on Predicitive Analytics with Python Course Objectives
Working in a hands-on learning environment, guided by our expert team, attendees will learn to:
- Understanding Predictive Analytics
- Python Data Analytics Ecosystem
- Advanced Predictive Modeling
- Deploying Predictive Models
- Stages of Predictive Analytics
- Problem Definition and Data Preparation
- Exploratory Data Analysis (EDA)
- Building Regression and Classification Models
- Neural Network Models with Keras
- Model Deployment as a Web Application
Prerequisites
Students should have skills at least equivalent to the following course(s) or should have attended as a pre-requisite:
- Fast Track to Python for Data Science
Audience
- This course is geared for Python experienced attendees who wish to learn and use basic machine learning algorithms and concepts.
Hands-on Predicitive Analytics with Python Outline
The Predictive Analytics Process
- Technical requirements
- What is predictive analytics?
- Reviewing important concepts of predictive analytics
- The predictive analytics process
- A quick tour of Python’s data science stack
Problem Understanding and Data Preparation
- Technical requirements
- Understanding the business problem and proposing a solution
- Practical project – diamond prices
- Practical project – credit card default
Dataset Understanding – Exploratory Data Analysis
- Technical requirements
- What is EDA?
- Univariate EDA
- Bivariate EDA
- Introduction to graphical multivariate EDA
Predicting Numerical Values with Machine Learning
- Technical requirements
- Introduction to ML
- Practical considerations before modeling
- MLR
- Lasso regression
- KNN
- Training versus testing error
Predicting Categories with Machine Learning
- Technical requirements
- Classification tasks
- Credit card default dataset
- Logistic regression
- Classification trees
- Random forests
- Training versus testing error
- Multiclass classification
- Naive Bayes classifiers
Introducing Neural Nets for Predictive Analytics
- Technical requirements
- Introducing neural network models
- Introducing TensorFlow and Keras
- Regressing with neural networks
- Classification with neural networks
- The dark art of training neural networks
Model Evaluation
- Technical requirements
- Evaluation of regression models
- Evaluation for classification models
- The k-fold cross-validation
Model Tuning and Improving Performance
- Technical requirements
- Hyperparameter tuning
- Improving performance
Implementing a Model with Dash
- Technical requirements
- Model communication and/or deployment phase
- Introducing Dash
- Implementing a predictive model as a web application
$2195.00
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3 Days Course |