fastkme : Faster Kaplan-Meier Estimator using JIT
The nonaprametric survival models like Nearest Neighbour, Kernel Survival, COBRA Survival or adaptive nearest neighbour require fitting kaplan meier estimato...
Posts by Tag
- Machine Learning 2
- Regression 2
- bayesians 1
- non-informative priors 1
- Tensorflow 1
- Scikit Learn 1
- Classification 1
- k-Nearest Neighbors 1
- ROC curve 1
- Linear Regression 1
- Logistic Regression 1
- Hyperparameter Tuning 1
- Confusion Matrix 1
- Ridge Regression 1
- Lasso Regression 1
- Logistic 1
- Bayesian 1
- HPDI 1
- Markov Chain 1
- MCMC 1
- Probability theory 1
- Survival Estimator 1
Machine Learning
Tensorflow Hello World
Tensorflow is made up of two words tensor and flow , where tensor means multidimensional array and flow means graph of operations. It is developed by google ...
Regression
Introduction to Logistic Regression
Usually in Linear Regression we consider $X$ as a explanatory variable whose columns are $X_1 , X_2 …..X_{p}$ are the variables which we use predict are the ...
Supervised Learning with Scikit Learn
Machine Learning is the art of giving computers the ability to learn from data and make decisions on their own without explicitly programmed for example ...
bayesians
Introduction To Non-Informative Priors
Prior density is denoted by $g(.)$ in this article Introduction Non-Informative Priors are the priors which we assume when we do not have any belief ab...
non-informative priors
Introduction To Non-Informative Priors
Prior density is denoted by $g(.)$ in this article Introduction Non-Informative Priors are the priors which we assume when we do not have any belief ab...
Tensorflow
Tensorflow Hello World
Tensorflow is made up of two words tensor and flow , where tensor means multidimensional array and flow means graph of operations. It is developed by google ...
Scikit Learn
Supervised Learning with Scikit Learn
Machine Learning is the art of giving computers the ability to learn from data and make decisions on their own without explicitly programmed for example ...
Classification
Supervised Learning with Scikit Learn
Machine Learning is the art of giving computers the ability to learn from data and make decisions on their own without explicitly programmed for example ...
k-Nearest Neighbors
Supervised Learning with Scikit Learn
Machine Learning is the art of giving computers the ability to learn from data and make decisions on their own without explicitly programmed for example ...
ROC curve
Supervised Learning with Scikit Learn
Machine Learning is the art of giving computers the ability to learn from data and make decisions on their own without explicitly programmed for example ...
Linear Regression
Supervised Learning with Scikit Learn
Machine Learning is the art of giving computers the ability to learn from data and make decisions on their own without explicitly programmed for example ...
Logistic Regression
Supervised Learning with Scikit Learn
Machine Learning is the art of giving computers the ability to learn from data and make decisions on their own without explicitly programmed for example ...
Hyperparameter Tuning
Supervised Learning with Scikit Learn
Machine Learning is the art of giving computers the ability to learn from data and make decisions on their own without explicitly programmed for example ...
Confusion Matrix
Supervised Learning with Scikit Learn
Machine Learning is the art of giving computers the ability to learn from data and make decisions on their own without explicitly programmed for example ...
Ridge Regression
Supervised Learning with Scikit Learn
Machine Learning is the art of giving computers the ability to learn from data and make decisions on their own without explicitly programmed for example ...
Lasso Regression
Supervised Learning with Scikit Learn
Machine Learning is the art of giving computers the ability to learn from data and make decisions on their own without explicitly programmed for example ...
Logistic
Introduction to Logistic Regression
Usually in Linear Regression we consider $X$ as a explanatory variable whose columns are $X_1 , X_2 …..X_{p}$ are the variables which we use predict are the ...
Bayesian
Highest Posterior Density Interval
Highest Posterior Density Interval is interval of the parmeter in which the posterir value are high when compared to any other point outside the interval (i....
HPDI
Highest Posterior Density Interval
Highest Posterior Density Interval is interval of the parmeter in which the posterir value are high when compared to any other point outside the interval (i....
Markov Chain
Convergence of Markov Chain
What is Markov Chain ? Markov Chain is a Stochastic Model in which Future is dependent only on Present not on Past , What I mean to say that is ...
MCMC
Convergence of Markov Chain
What is Markov Chain ? Markov Chain is a Stochastic Model in which Future is dependent only on Present not on Past , What I mean to say that is ...
Probability theory
Probability Theory (Series)
This series is an introduction to Probability Theory, It closely follows the book “Probability Essentials” by Jean Jacod and Philip Protter. Day 0 : Phi...
Survival Estimator
fastkme : Faster Kaplan-Meier Estimator using JIT
The nonaprametric survival models like Nearest Neighbour, Kernel Survival, COBRA Survival or adaptive nearest neighbour require fitting kaplan meier estimato...