Канал: MachineLearningInterview

Batch Gradient Descent vs Mini-Batch Gradient Descent vs Stochastic Gradient Descent

Batch Gradient Descent vs Mini-Batch Gradient Descent vs Stochastic Gradient Descent

What is Layer Normalization ?

What is Layer Normalization ?

Batch Normalization in Deep Neural Networks

Batch Normalization in Deep Neural Networks

Normalization in Deep Neural Network

Normalization in Deep Neural Network

What is the Median Absolute Deviation (MAD)?

What is the Median Absolute Deviation (MAD)?

Some Risks of Building with LLMs and Generative AI

Some Risks of Building with LLMs and Generative AI

Gower Distance for Mixed Data

Gower Distance for Mixed Data

Understanding Mixed Data

Understanding Mixed Data

SMOTE for Handling Imbalanced Datasets

SMOTE for Handling Imbalanced Datasets

Inverse Propensity Weighing (IPW)

Inverse Propensity Weighing (IPW)

What is Rejection Sampling?

What is Rejection Sampling?

Correlation vs Causation

Correlation vs Causation

Techniques for Anomaly Detection

Techniques for Anomaly Detection

Z-Score for Outlier Detection

Z-Score for Outlier Detection

METEOR : A metric for Machine Translation

METEOR : A metric for Machine Translation

BLEU Score for evaluating text generation NLP tasks

BLEU Score for evaluating text generation NLP tasks

Machine Translation: An Overview

Machine Translation: An Overview

Interpretable AI: Global vs Local Interpretability

Interpretable AI: Global vs Local Interpretability

Global Surrogate Model for Interpretable AI

Global Surrogate Model for Interpretable AI

Complement Naive Bayes Classifier

Complement Naive Bayes Classifier

Do we need Optimization for Machine Learning?

Do we need Optimization for Machine Learning?

Why learn Linear Algebra for Machine Learning

Why learn Linear Algebra for Machine Learning

Voting, Averaging & Stacking Multiple ML Models: Ensemble Learning

Voting, Averaging & Stacking Multiple ML Models: Ensemble Learning

Why do we need Probability and Statistics to build Machine Learning Models?

Why do we need Probability and Statistics to build Machine Learning Models?

Fairness in Machine Learning : Metrics based on Confusion Matrix

Fairness in Machine Learning : Metrics based on Confusion Matrix

How to Optimize Pandas Code?

How to Optimize Pandas Code?

Should I Transition to a Data Science Career ?

Should I Transition to a Data Science Career ?

Learning Math For ML

Learning Math For ML

The Page Rank Algorithm

The Page Rank Algorithm

Monty Hall Problem - Probability and Statistics

Monty Hall Problem - Probability and Statistics

Covariance and Correlation

Covariance and Correlation

How to find Optimal K with K-means Clustering ? The Elbow and Silhouette methods

How to find Optimal K with K-means Clustering ? The Elbow and Silhouette methods

Debiasing word embeddings in NLP Applications

Debiasing word embeddings in NLP Applications

PrepTool Pro to crack Machine LearninIg Interviews

PrepTool Pro to crack Machine LearninIg Interviews

Locality Sensitive Hashing For efficient Nearest Neighbour Search

Locality Sensitive Hashing For efficient Nearest Neighbour Search

Machine Learning Product Development LifeCycle

Machine Learning Product Development LifeCycle

Elastic Net Regularization For Regression

Elastic Net Regularization For Regression

Anomaly detection with Isolation Forests

Anomaly detection with Isolation Forests

Top Three Deep Learning Myths

Top Three Deep Learning Myths

One-Class SVM for Outlier Detection

One-Class SVM for Outlier Detection

What is AUC ?

What is AUC ?

Can we compute AUC Metric for an SVM classifier ?

Can we compute AUC Metric for an SVM classifier ?

What are the popular activation functions used in a neural network? Deep Learning DID Series: part 3

What are the popular activation functions used in a neural network? Deep Learning DID Series: part 3

When does it make sense to use deep learning ? : Deep Learning DID Series - part 1

When does it make sense to use deep learning ? : Deep Learning DID Series - part 1

PrepTool Basic to revise concepts on MachineLearningInterview.com

PrepTool Basic to revise concepts on MachineLearningInterview.com

Explain Logistic Regression ? : Data Science Interviews Decoded

Explain Logistic Regression ? : Data Science Interviews Decoded

How do you predict with Logistic Regression ? : Data Science Interviews Decoded

How do you predict with Logistic Regression ? : Data Science Interviews Decoded

What are the various kinds of Data Science Roles ?

What are the various kinds of Data Science Roles ?

What are the various rounds in an interview for a Data Scientist Position ?

What are the various rounds in an interview for a Data Scientist Position ?

Are algorithms and data structures important for Data Scientist Interview ?

Are algorithms and data structures important for Data Scientist Interview ?

What does the typical day of a data scientist look like ?

What does the typical day of a data scientist look like ?

Explain How linear regression works ? (3 minutes)

Explain How linear regression works ? (3 minutes)

How to answer : Explain Linear Regression ?

How to answer : Explain Linear Regression ?

NLP Tutorial : Automatic Question Answering From FAQs

NLP Tutorial : Automatic Question Answering From FAQs