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Supervised Machine Learning with Python
Supervisedmachinelearningisusedinawiderangeofsectors(suchasfinance,onlineadvertising,andanalytics)becauseitallowsyoutotrainyoursystemtomakepricingpredictions,campaignadjustments,customerrecommendations,andmuchmorewhilethesystemself-adjustsandmakesdecisionsonitsown.Asaresult,it'scrucialtoknowhowamachine"learns"underthehood.Thisbookwillguideyouthroughtheimplementationandnuancesofmanypopularsupervisedmachinelearningalgorithmswhilefacilitatingadeepunderstandingalongtheway.You’llembarkonthisjourneywithaquickoverviewandseehowsupervisedmachinelearningdiffersfromunsupervisedlearning.Next,weexploreparametricmodelssuchaslinearandlogisticregression,non-parametricmethodssuchasdecisiontrees,andvariousclusteringtechniquestofacilitatedecision-makingandpredictions.Asweproceed,you'llworkhands-onwithrecommendersystems,whicharewidelyusedbyonlinecompaniestoincreaseuserinteractionandenrichshoppingpotential.Finally,you’llwrapupwithabriefforayintoneuralnetworksandtransferlearning.Bytheendofthisbook,you’llbeequippedwithhands-ontechniquesandwillhavegainedthepracticalknow-howyouneedtoquicklyandpowerfullyapplyalgorithmstonewproblems.
目錄(105章)
倒序
- coverpage
- Title Page
- Copyright and Credits
- Supervised Machine Learning with Python
- About Packt
- Why subscribe?
- Packt.com
- Contributor
- About the author
- Packt is searching for authors like you
- Preface
- Who this book is for
- What this book covers
- To get the most out of this book
- Download the example code files
- Download the color images
- Conventions used
- Get in touch
- Reviews
- First Step Towards Supervised Learning
- Technical requirements
- An example of supervised learning in action
- Logistic regression
- Setting up the environment
- Supervised learning
- Hill climbing and loss functions
- Loss functions
- Measuring the slope of a curve
- Measuring the slope of an Nd-curve
- Measuring the slope of multiple functions
- Hill climbing and descent
- Model evaluation and data splitting
- Out-of-sample versus in-sample evaluation
- Splitting made easy
- Summary
- Implementing Parametric Models
- Technical requirements
- Parametric models
- Finite-dimensional models
- The characteristics of parametric learning algorithms
- Parametric model example
- Implementing linear regression from scratch
- The BaseSimpleEstimator interface
- Logistic regression models
- The concept
- The math
- The logistic (sigmoid) transformation
- The algorithm
- Creating predictions
- Implementing logistic regression from scratch
- Example of logistic regression
- The pros and cons of parametric models
- Summary
- Working with Non-Parametric Models
- Technical requirements
- The bias/variance trade-off
- Error terms
- Error due to bias
- Error due to variance
- Learning curves
- Strategies for handling high bias
- Strategies for handling high variance
- Introduction to non-parametric models and decision trees
- Non-parametric learning
- Characteristics of non-parametric learning algorithms
- Is a model parametric or not?
- An intuitive example – decision tree
- Decision trees – an introduction
- How do decision trees make decisions?
- Decision trees
- Splitting a tree by hand
- If we split on x1
- If we split on x2
- Implementing a decision tree from scratch
- Classification tree
- Regression tree
- Various clustering methods
- What is clustering?
- Distance metrics
- KNN – introduction
- KNN – considerations
- A classic KNN algorithm
- Implementing KNNs from scratch
- KNN clustering
- Non-parametric models – pros/cons
- Pros of non-parametric models
- Cons of non-parametric models
- Which model to use?
- Summary
- Advanced Topics in Supervised Machine Learning
- Technical requirements
- Recommended systems and an introduction to collaborative filtering
- Item-to-item collaborative filtering
- Matrix factorization
- Matrix factorization in Python
- Limitations of ALS
- Content-based filtering
- Limitations of content-based systems
- Neural networks and deep learning
- Tips and tricks for training a neural network
- Neural networks
- Using transfer learning
- Summary
- Other Books You May Enjoy
- Leave a review - let other readers know what you think 更新時間：2021-06-24 14:01:20
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