A Markov chain is known as a stochastic model which describes some sequence of possible events in which the probability of each event depends only on the state from the previous event. Markov chains are used widely in our modern world in many modelling scenarios, so it's certainly helpful to know this as your refresh on topics for a Data Science interview.

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Knowing about GANs in deep learning is crucial to understand since they can generate new and realistic data!

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- Distributions

- Statistics

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Multicollinearity is a concept that comes up quite frequently in Data Science interviews in my experience, so make sure you take some time to review these concepts before your next technical!

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- Transformers in NLP

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- Distributions

- Statistics

- A/B Testing

- ROC-AUC

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If you're new to the world of data, you might be curious about what role is right for you - Data Scientist, Analyst, or Machine Learning Engineer. This bonus episode deviates from our usual content to help you get a rough picture of the differences (and similarities) between these roles.

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- Imbalanced Data

- The Bias-Variance Tradeoff

- Transformers in NLP

- Self-Attention in NLP

- Distributions

- Statistics

- A/B Testing

- ROC-AUC

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Activation functions are an important part of neural networks, so knowing them helps you build smarter models!

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Becoming a premium member also gives you access to our locked episodes, which include helpful content such as:

- NLP

- Deep Learning

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- Imbalanced Data

- The Bias-Variance Tradeoff

- Transformers in NLP

- Self-Attention in NLP

- Distributions

- Statistics

- A/B Testing

- ROC-AUC

.... and so much more!

Hyperparameter tuning is a must know if you want to understand data science model optimization!

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Becoming a premium member also gives you access to our locked episodes, which include helpful content such as:

- NLP

- Deep Learning

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- Imbalanced Data

- The Bias-Variance Tradeoff

- Transformers in NLP

- Self-Attention in NLP

- Distributions

- Statistics

- A/B Testing

- ROC-AUC

.... and so much more!

Mastering the Central Limit Theorem in data science interviews helps you shine with solid statistical prowess! Make sure you brush up on this common statistical concept before your next interview.

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Becoming a premium member also gives you access to our locked episodes, which include helpful content such as:

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- Imbalanced Data

- The Bias-Variance Tradeoff

- Transformers in NLP

- Self-Attention in NLP

- Distributions

- Statistics

- A/B Testing

- ROC-AUC

.... and so much more!

CI/CD in Data Science and ML helps get models from idea to deployment faster and with fewer errors! If you're interested in production ML, be sure to check out this episode for high-level overview into CI/CD.

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Becoming a premium member also gives you access to our locked episodes, which include helpful content such as:

- NLP

- Deep Learning

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- Imbalanced Data

- The Bias-Variance Tradeoff

- Transformers in NLP

- Self-Attention in NLP

- Distributions

- Statistics

- A/B Testing

- ROC-AUC

.... and so much more!

As a data scientist, knowing about multi-armed bandits is pretty handy because they're a go-to tool for optimizing decisions with limited resources!

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Becoming a premium member also gives you access to our locked episodes, which include helpful content such as:

- NLP

- Deep Learning

- Recurrent Neural Networks

- Imbalanced Data

- The Bias-Variance Tradeoff

- Transformers in NLP

- Self-Attention in NLP

- Distributions

- Statistics

- A/B Testing

- ROC-AUC

.... and so much more!

K-Nearest Neighbours is a common classification algorithm in machine learning. Be sure to refresh your knowledge on this model in your interview prep journey!

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Becoming a premium member also gives you access to our locked episodes, which include helpful content such as:

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- Deep Learning

- Recurrent Neural Networks

- Imbalanced Data

- The Bias-Variance Tradeoff

- Transformers in NLP

- Self-Attention in NLP

- Distributions

- Statistics

- A/B Testing

- ROC-AUC

.... and so much more!