Exhaustive vs Non-exhaustive Cross-Validation in Machine Learning is a short video to discuss the two types of cross-validation techniques that we have in machine learning https://youtu.be/WbOTf3ugeYA Exhaustive vs Non-exhaustive Cross-Validation in Machine Learning Happy Learning !!
How to use K Fold Cross-Validation for Imbalanced Dataset is a short video to discuss cross-validation for Imbalanced Dataset. It requires the knowledge of Nested K-Fold Cross-Validation, Non-Nested K-Fold Cross-Validation, Stratified K-Fold Cross-Validation, Exhaustive Cross-Validation. https://youtu.be/2G9s9-BPjjI K-Fold Cross-Validation for Imbalanced Dataset Happy Learning !!
Cross-Validation Advantages and Disadvantages in Machine Learning is a short video to discuss the main Advantages and Disadvantages of the Cross-Validation technique in Machine Learning. https://youtu.be/ScSQcDjgmlY Cross-Validation Advantages and Disadvantages in Machine Learning Happy Learning !!
Types of Output a Deep Learning Model can Produce is a short video to discuss the possible outputs from a Deep Learning Model. Generative Adversarial Network(GAN) possible outputs are also discussed. This is a part of the Machine Learning Interview Question. https://youtu.be/FSDgjU9BPJo Types of Output a Deep Learning Model can Produce Happy Learning !!
Cross-Validation in Machine Learning for example K-fold Cross-Validation is a short video to describe what is Cross-Validation in Machine Learning, why do we need to do cross-validation, and how to do it using sklearn. https://youtu.be/9YqhJUSWSj8 Cross-Validation in Machine Learning and K-fold Cross-Validation using Sklearn Happy Learning !!
Computational complexity of self-attention layers grows very much as a function of sequence length. please watch the below video for more details: What is Self Attention Bottleneck for Transformers Deep Learning Models https://youtu.be/ByYaJ3k0SAY
This post is not to discourage any one :)The aim of this post is to discuss, if you have started learning or planning to learn Python programming, are you on the right path?I don't think that there's a lot of good uses NOT to learn something, however, the argument is "could my time be better … Continue reading Top Ten Reasons for NOT learning Python Programming
This Post is not to discourage any one :)But at the same time we all should discuss the reality.The aim of this post is to discuss, if you have started learning or planning to learn machine learning, are you on the right path?The conclusion of right or wrong path completely depends on the individualAlright, so … Continue reading Top Ten Reasons for NOT learning Machine Learning and Artificial Intelligence
https://youtu.be/KQH4PSF4AjE Normal Distribution vs Probability Distribution Function vs Bell Curve in Statistics In Statistics, the probability distribution function is a function that takes the values of a feature as input.The output of the probability distribution function is the probability of the values the feature can take. Therefore we can make predictions based on the probability distribution function. A normal … Continue reading Normal Distribution and Probability Distribution in Statistics
Random forest machine learning is an algorithm that consists of many decision trees.In the Random Forest model, there are more than one decision tree models.Random forest algorithm can be used for both classification and regression problems. Prediction using Random forest classification modelClassification: Each individual tree in the random forest classification, predicts a class and the … Continue reading What is RANDOM in Random Forest Machine Learning Algorithm