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Course Outline
- Introduction to ML
- Machine learning as part of Artificial intelligence
- Types of ML
- ML algorithms
- Challenges and potential use of ML
- Overfitting and bias-variance trade-off in ML
- Techniques of Machine learning
- The Machine Learning Workflow
- Supervised learning – Classification, Regression
- Unsupervised learning – Clustering, Anomaly detection
- Semi-supervised learning and Reinforcement Learning
- Consideration in Machine Learning
- Data Preprocessing
- Data preparation and transformation
- Feature engineering
- Feature Scaling
- Dimensionality reduction and variable selection
- Data visualization
- Exploratory analysis
- Case studies
- Advanced feature engineering and impact on results in linear regression for prediction
- Time series analysis and Forecasting monthly volume of sales - basic methods, seasonal adjustment, regression, exponential smoothing, ARIMA, neural networks
- Market basket analysis and association rules mining
- Segmentation analysis using clustering and self-organising maps
- Classification which customer is likely to default using logistic regression, decision trees, xgboost, svm
Requirements
Knowledge and awareness of Machine Learning fundmentals
14 Hours
Delivery Options
Private Group Training
Our identity is rooted in delivering exactly what our clients need.
- Pre-course call with your trainer
- Customisation of the learning experience to achieve your goals -
- Bespoke outlines
- Practical hands-on exercises containing data / scenarios recognisable to the learners
- Training scheduled on a date of your choice
- Delivered online, onsite/classroom or hybrid by experts sharing real world experience
Private Group Prices RRP from €4560 online delivery, based on a group of 2 delegates, €1440 per additional delegate (excludes any certification / exam costs). We recommend a maximum group size of 12 for most learning events.
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Public Training
Please see our public courses
Testimonials (2)
the ML ecosystem not only MLFlow but Optuna, hyperops, docker , docker-compose
Guillaume GAUTIER - OLEA MEDICAL
Course - MLflow
I enjoyed participating in the Kubeflow training, which was held remotely. This training allowed me to consolidate my knowledge for AWS services, K8s, all the devOps tools around Kubeflow which are the necessary bases to properly tackle the subject. I wanted to thank Malawski Marcin for his patience and professionalism for training and advice on best practices. Malawski approaches the subject from different angles, different deployment tools Ansible, EKS kubectl, Terraform. Now I am definitely convinced that I am going into the right field of application.
