Tag: algorithm

ML vs DL

Machine Learning modifies an algorithm without any human intervention by using structured data. Deep Learning, on the other hand, tries to imitate the human brain by using artificial neurons that form different interpretations of the same data. Based on these interpretations the best possible answer is arrived at. In simple words, if a Machine learning…
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Understanding the Bias-Variance Trade-off

George Box once said, “All models are wrong, but some are useful.” From a supervised machine learning perspective, all models have errors, and to make our models useful, we have to minimize such errors. More specifically, we have to minimize two major sources of error: bias and variance. Prior to applying a machine learning algorithm,…
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Decision made Easy with Random Forest!!!

When We, Human always want to have a second opinion why not our algorithms? Random forests or random decision forests are an ensemble learning method for classification, regression and other tasks that operates by constructing a multitude of decision trees at training time and outputting the class that is the mode of the classes (classification) or mean prediction (regression) of the individual trees. Let’s understand decision tree…
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Discuss the trade off between bias and variance

Bias is error due to erroneous or overly simplistic assumptions in the learning algorithm you’re using. This can lead to the model underfitting your data, making it hard for it to have high predictive accuracy and for you to generalize your knowledge from the training set to the test set. Variance is error due to too much…
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Bias/Variance Trade-off

Bias/Variance trade-off is an important concept in learning theory. This post discusses topic from both – theoretical and practical perspective. General Main goal of any learning algorithm is to predict and generalise well. More formally, this goal is equivalent to ‘minimise expected error on unseen data’ – thus taking closer look at the components of…
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The Awesomeness of Viterbi

Automatic Speech Recognition (ASR) refers to the task of automatically convert a speech signal into text. Nowadays, we all use this marvelous technology without even wonder about its complexity. Currents state of the art system are based on different Deep Neural Networks Architectures (the most basic one is the hybrid Deep Neural Network- Hidden Markov Model (DNN-HMM))…
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Why you should not blindly trust your deep learning algorithm?

Why you should not blindly trust your deep learning algorithm? Deep learning is the new poster boy in the world of data science. It has become the heart of of designing intelligent systems. However, all that glitters is not gold! There are surprisingly a few limitations to the deep learning models. Let us explore them…
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Predictive Algorithm to identify Medication Adherence/Non Adherence Pattern in chronically ill individuals

Medication adherence is defined by the World Health Organization as “the degree to which the person’s behavior corresponds with the agreed recommendations from a health care provider.”[1] Poor adherence to prescribed regimens can result in serious health consequences. For instance, a recent study found that the risk of hospitalization was more than double in patients with…
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Its not just about the science

It’s true that all data scientists need to have good analytical abilities, and expertise with the tools, languages and packages that enable them to do what they do. There are 3 other qualities that make a great data scientist, which are not about the ‘science’ in Data Science: It’s not about the tools: A great…
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