A confusion matrix is a method of summarizing a classification algorithm’s performance. It is simply a summarized table of the number of correct and incorrect predictions. As you know in supervised machine learning algorithms, we train the model on the training dataset and then use the testing data to make predictions. For the regression model, …
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Career Misconceptions Mathematics of Machine Learning- Understanding the underlying mathematics of machine learning algorithms. Importance of Statistical Thinking- Why knowing statistics and even thinking statistics is important. Defining The Data Scientist Role- Exactly what is a Data Scientist’s responsibilities and why they vary so much across organizations. 1. The Mathematics Behind Machine Learning Algorithms Python …
In this tutorial we are going to learn about the difference between over-fitting and under-fitting in machine learning with the help of the Python Programming library ScikitLearn, also known as SkLearn. Understanding Undrfitting One important task in machine learning is constructing statistical models. You would like to model the data as accurately as possible, but …
When most Americans hear the phrase Artificial Intelligence or Machine Learning they immediately think of “Sky Net”, “The Matrix”, or “iRobot”. The inevitable battle of Man vs. Machine… Yet, most people aren’t fully aware of what machine learning is, how it affects their day-to-day lives, or even how it can benefit them. Machine Learning is …
All Machine Learning Algorithms You Need To Know in 2023 Read More »
Machine learning teaches computers to find patterns in data. If you’re working with large numerical datasets, it’s natural to store data in a matrix format. Each row in the matrix represents a different observation, and each column represents a different attribute of that observation. It shouldn’t be surprising, then, that linear algebra underlies many machine …
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Machine learning algorithms are often mistaken as objective analytics and decision-making solutions to human inefficiencies. Paradoxically, humans often make machine learning algorithms inefficient by way of biases. These biases include sample bias, reporting bias, prejudice bias, confirmation bias, group attribution bias, algorithm bias, measurement bias, recall bias, exclusion bias, and automation bias. Machine learning is …
A time series is a sequence of data points collected over time. In many domains, there is always a need to deal with multivariate time series data, such as a network of sensors measuring weather conditions, or multiple financial indices reflecting global economics. Due to the nature of non-stationary and complicated correlation, it is a …
Stock Market Prediction with Multivariate Time Series in Python using Keras Read More »
Can a machine classify handwritten digits better than the human brain? Let’s see if Convolutional Neural Networks can give us some insight into this matter, then we’ll let you be the judge. To add some context for Convolutional Neural Networks, we’ll begin the tutorial with a practical example of a neural network. A Convolutional Neural …
