Classroom course

Machine Learning and Predictive Analytics
in Marketing


Classroom course

Machine Learning and Predictive Analytics in Marketing


REQUEST INFORMATION
Price
1.430 € + VAT

Duration
16 hours

Date:
September 22th-23th

Qualification obtained
Certificate

Course code
AGSAI006

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The large amount of data that can be collected today from customers is revolutionizing various sectors, including the one of Marketing. Through Machine Learning algorithms it is possible to optimize the customer satisfaction, predict their behaviour and probability of "churning", measure their "lifetime-value" and grouping customers into "non-traditional" clusters in order to propose targeted campaigns.

Who is it for?

The course is aimed at:

  • programmers
  • graduate students who know programming
Prerequisites

Mandatory in order to partecipate:

  • have the basics of Machine Learning (eg learning supervised, neural networks, cost functions etc.)
  • learn about the construction of Machine Learning models with Python
  • know the fundamentals of Probability Theory
Objective

The aim of this course is to present the latest architectures and their application on concrete problems: facial recognition, segmentation and identification of objects.

Program
  • 1. CNN
    • 1.1 Convolutional layer
    • 1.2 Padding
    • 1.3 Pooling layer
    • 1.4 Strided Convolutions
  • 2. Deep CNN models
    • 2.1 ResNet
    • 2.2 Inception
    • 2.3 MobileNet
    • 2.4 EfficientNet
    • 2.5 Transfer Learning
  • 3. Object Detection
    • 3.1 Object Localization
    • 3.2 Landmark Detection
    • 3.3 Object Detection
    • 3.4 YOLO
    • 3.5 Semantic Segmentation
    • 3.5 U-Net
  • 4. Facial Recognition
    • 4.1 One shot Learning
    • 4.2 Siamese Network
    • 4.3 Facial Check
Classroom and safety rules
To comply with Covid safety regulations, the classroom will be equipped with special filtering systems special air filtering systems and participation will be limited to a maximum of 8 participants with a green pass. The course will be confirmed upon reaching the minimum number of 4 participants.

The large amount of data that can be collected today from customers is revolutionizing various sectors, including the one of Marketing. Through Machine Learning algorithms it is possible to optimize the customer satisfaction, predict their behaviour and probability of "churning", measure their "lifetime-value" and grouping customers into "non-traditional" clusters in order to propose targeted campaigns.

Who is it for?

The course is aimed at:

  • programmers
  • graduate students who know programming
Prerequisites

Mandatory in order to partecipate:

  • have the basics of Machine Learning (eg learning supervised, neural networks, cost functions etc.)
  • learn about the construction of Machine Learning models with Python
  • know the fundamentals of Probability Theory
Objective

The aim of this course is to present the latest architectures and their application on concrete problems: facial recognition, segmentation and identification of objects.

Program
  • 1. CNN
    • 1.1 Convolutional layer
    • 1.2 Padding
    • 1.3 Pooling layer
    • 1.4 Strided Convolutions
  • 2. Deep CNN models
    • 2.1 ResNet
    • 2.2 Inception
    • 2.3 MobileNet
    • 2.4 EfficientNet
    • 2.5 Transfer Learning
  • 3. Object Detection
    • 3.1 Object Localization
    • 3.2 Landmark Detection
    • 3.3 Object Detection
    • 3.4 YOLO
    • 3.5 Semantic Segmentation
    • 3.5 U-Net
  • 4. Facial Recognition
    • 4.1 One shot Learning
    • 4.2 Siamese Network
    • 4.3 Facial Check
Classroom and safety rules
To comply with Covid safety regulations, the classroom will be equipped with special filtering systems special air filtering systems and participation will be limited to a maximum of 8 participants with a green pass. The course will be confirmed upon reaching the minimum number of 4 participants.
REQUEST INFORMATION
Price
1.430 € + VAT

Duration
16 hours

Date:
September 22th-23th

Qualification obtained
Certificate

Course code
AGSAI006

subscribe