Python Machine Learning A Step-by-Step Journey with Scikit-Learn and Tensorflow for Beginners

**Are you a budding programmer eager to delve into the realm of Python Machine Learning? Does the prospect of transitio

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Table of contents :
INTRODUCTION
CHAPTER A1:
UNSUPERVISED AMACHINE ALEARNING
Principal AComponent AAnalysis
k-means AClustering
CHAPTER A2:
DEEP ABELIEF ANETWORKS
Neural ANetworks
The ARestricted ABoltzmann AMachine
Constructing ADeep ABelief ANetworks
CHAPTER A3:
CONVOLUTIONAL ANEURAL ANETWORKS
Understanding Athe AArchitecture
Connecting Athe APieces
CHAPTER A4:
STACKED ADENOISING AAUTOENCODERS
Autoencoders
CHAPTER A5:
SEMI-SUPERVISED ALEARNING
Understanding Athe ATechniques
Self-learning
Contrastive APessimistic ALikelihood AEstimation
CHAPTER A6:
TEXT AFEATURE AENGINEERING
Text AData ACleaning
Building AFeatures
CHAPTER A7:
MORE AFEATURE AENGINEERING
Creating AFeature ASets
Real-world AFeature AEngineering
CHAPTER A8:
ENSEMBLE AMETHODS
Averaging AEnsembles
Stacking AEnsembles
CONCLUSION

Python Machine Learning A Step-by-Step Journey with Scikit-Learn and Tensorflow for Beginners

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