pattern-recognition-and-machine-learning

I implement the algorithm of the bishop's the book pattern recognition and machine learning , and workin with real data

Name		Name	Last commit message	Last commit date
.github/workflows		.github/workflows
Chapter 2 : Probability Distributions		Chapter 2 : Probability Distributions
Chapter 4:LinearModelsForClassification		Chapter 4:LinearModelsForClassification
Chapter 5:Neural Networks		Chapter 5:Neural Networks
Chapter1:Introduction		Chapter1:Introduction
Chapter3:LinearModelsForRegression		Chapter3:LinearModelsForRegression
Chapter9:Mixture And Models With EM		Chapter9:Mixture And Models With EM
Chapter08 MRF-Ising-Model.ipynb		Chapter08 MRF-Ising-Model.ipynb
Clustering.ipynb		Clustering.ipynb
DS_K_Nearst_Neighbours.ipynb		DS_K_Nearst_Neighbours.ipynb
Gaussian_Process1.ipynb		Gaussian_Process1.ipynb
LinearModelsForClassification		LinearModelsForClassification
Linear_Models_For_Regression.ipynb		Linear_Models_For_Regression.ipynb
Logistic_Regression (1).ipynb		Logistic_Regression (1).ipynb
Machine_Learning's_Concepts.ipynb		Machine_Learning's_Concepts.ipynb
MySQL.ipynb		MySQL.ipynb
Neurals_Networks.ipynb		Neurals_Networks.ipynb
PolynomialRegression.py		PolynomialRegression.py
README.md		README.md
Weather-Prediction.ipynb		Weather-Prediction.ipynb
dnns-with-keras.ipynb		dnns-with-keras.ipynb
gaussian-distribution.ipynb		gaussian-distribution.ipynb
generated_file.c		generated_file.c
img.jpeg		img.jpeg
n_gram.ipynb		n_gram.ipynb
pca.pyx		pca.pyx
polynomialregression.ipynb		polynomialregression.ipynb
svm.c		svm.c

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