Why Deep Learning Compilers like TensorFlow XLA TVM is needed is a short video to discuss that to alleviate the burden of optimizing the deep learning models on each deep learning hardware manually, the deep learning engineers use the DL compilers. Happy Learning !!
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 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. 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. 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. 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. 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
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…
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…
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 distribution function is a special case of a probability distribution function that looks…
