Data Science Interview Prep : Recent Episodes
Tech MLab
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As a data science professional, I know firsthand how challenging it can be to navigate the job market and prepare for interviews. That's why I started this podcast - to provide valuable resources to those looking to break into the field of data science.
Running a podcast takes a lot of time and effort, so please consider supporting us on Patreon: https://www.patreon.com/user?u=84843123
As a data science professional, I know firsthand how challenging it can be to navigate the job market and prepare for interviews. That's why I started this podcast - to provide valuable resources to those looking to break into the field of data science.Running a podcast takes a lot of time and effort, so please consider supporting us.
Become a Paid Subscriber: https://podcasters.spotify.com/pod/show/data-science-interview/subscribe
This is a high-level episode on collaborative filtering; no math, just the intuition! Let us know if you'd like a more technical overview in the future.
Want to fine-tune an LLM? Learn about LoRA for efficient fine-tuning!
Become a Paid Subscriber: https://podcasters.spotify.com/pod/show/data-science-interview/subscribe
As a data science professional, I know firsthand how challenging it can be to navigate the job market and prepare for interviews. That's why I started this podcast - to provide valuable resources to those looking to break into the field of data science.Running a podcast takes a lot of time and effort, so please consider supporting us.
Become a Paid Subscriber: https://podcasters.spotify.com/pod/show/data-science-interview/subscribe
As a data science professional, I know firsthand how challenging it can be to navigate the job market and prepare for interviews. That's why I started this podcast - to provide valuable resources to those looking to break into the field of data science.
Running a podcast takes a lot of time and effort, so please consider supporting us.
Become a Paid Subscriber: https://podcasters.spotify.com/pod/show/data-science-interview/subscribe
As you may have noticed, The Data Science Interview Prep Podcast has been away for a few months.
Here's why!
Now, we're back on track and ready to help you prepare for your next big interview in all things Data Science.
Apologies we were a little delayed on getting this episode out. We had some account issues, but hope you enjoy the episode!This episode will be available as free for a limited time.
Want to support us?https://podcasters.spotify.com/pod/show/data-science-interview/subscribe
Want to support us?
Become a premium subscriber to The Data Science Interview Prep Podcast: https://podcasters.spotify.com/pod/show/data-science-interview/subscribe
Want to support us?
Become a premium subscriber to The Data Science Interview Prep Podcast: https://podcasters.spotify.com/pod/show/data-science-interview/subscribe
Want to support us?
Become a premium subscriber to The Data Science Interview Prep Podcast: https://podcasters.spotify.com/pod/show/data-science-interview/subscribe
Want to support us?
Become a premium subscriber to The Data Science Interview Prep Podcast: https://podcasters.spotify.com/pod/show/data-science-interview/subscribe
Want to support us?
Become a premium subscriber to The Data Science Interview Prep Podcast: https://podcasters.spotify.com/pod/show/data-science-interview/subscribe
Want to support us?
Become a premium subscriber to The Data Science Interview Prep Podcast: https://podcasters.spotify.com/pod/show/data-science-interview/subscribe
Check out this high-level overview into the Hadoop ecosystem!
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Become a premium subscriber to The Data Science Interview Prep Podcast: https://podcasters.spotify.com/pod/show/data-science-interview/subscribe
Check out one of our popular past episodes on the classic, Word2Vec!
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We're adding applied topics to our episode roster - let us know what you think in the comments. In this episode, we discuss how to apply data science to customer segmentation.
Become a Paid Subscriber to access our full library on Spotify: https://podcasters.spotify.com/pod/show/data-science-interview/subscribe
Reinforcement learning is all around us - from playing Go to building robots. To unlock this episode, become a premium subscriber today!
Become a Paid Subscriber for access to the full Data Science Interview Prep Podcast library: https://podcasters.spotify.com/pod/show/data-science-interview/subscribe
If you enjoy our podcast, please consider becoming a premium member on eitherPatreon ($5 donation) orSpotify ($2.99 donation).
Your donation goes directly to supporting this channel and the human labor that goes into each of these episodes. For each episode, we do research and fact-check our content to make sure that you get the best information possible, even on cutting edge topics. Become a Paid Subscriber: https://podcasters.spotify.com/pod/show/data-science-interview/subscribe
Let's jump into statistics and understand how we can ensure our results are truly significant!
Become a Paid Subscriber for access to the full Data Science Interview Prep Podcast library: https://podcasters.spotify.com/pod/show/data-science-interview/subscribe
If you enjoy our podcast, please consider becoming a premium member on eitherPatreon ($5 donation) orSpotify ($2.99 donation).
Your donation goes directly to supporting this channel and the human labor that goes into each of these episodes. For each episode, we do research and fact-check our content to make sure that you get the best information possible, even on cutting edge topics. Become a Paid Subscriber: https://podcasters.spotify.com/pod/show/data-science-interview/subscribe
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!
SHAP is an important concept to understand in the world of model transparency. Make sure to brush up on this concept to be able to clearly communicate your findings!
Become a Paid Subscriber for access to the full Data Science Interview Prep Podcast library: https://podcasters.spotify.com/pod/show/data-science-interview/subscribe
If you enjoy our podcast, please consider becoming a premium member on eitherPatreon ($5 donation) orSpotify ($2.99 donation).
Your donation goes directly to supporting this channel and the human labor that goes into each of these episodes. For each episode, we do research and fact-check our content to make sure that you get the best information possible, even on cutting edge topics. Become a Paid Subscriber: https://podcasters.spotify.com/pod/show/data-science-interview/subscribe
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!
Are you interviewing to become a Product Data Scientist? Or are you looking to understand associations between your data? If so, make sure to understand Chi-Square, a fundamental statistical topic.
Become a Paid Subscriber for access to the full Data Science Interview Prep Podcast library: https://podcasters.spotify.com/pod/show/data-science-interview/subscribe
If you enjoy our podcast, please consider becoming a premium member on eitherPatreon ($5 donation) orSpotify ($2.99 donation).
Your donation goes directly to supporting this channel and the human labor that goes into each of these episodes. For each episode, we do research and fact-check our content to make sure that you get the best information possible, even on cutting edge topics. Become a Paid Subscriber: https://podcasters.spotify.com/pod/show/data-science-interview/subscribe
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!
SVMs are one of those foundational models that are a must-know in Data Science!
Become a Paid Subscriber for access to our full library: https://podcasters.spotify.com/pod/show/data-science-interview/subscribe
If you enjoy The Data Science Interview Prep Podcast, please consider becoming a premium member on either Patreon ($5 donation) or Spotify ($2.99 donation). Your donation goes directly to supporting this channel and the human labor that goes into each of these episodes. For each episode, we do research and fact-check our content to make sure that you get the best information possible, even on cutting edge topics. Become a Paid Subscriber: https://podcasters.spotify.com/pod/show/data-science-interview/subscribe
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!
Mock Interview II
Become a Paid Subscriber for access to our full library: https://podcasters.spotify.com/pod/show/data-science-interview/subscribe
If you enjoy our podcast, please consider becoming a premium member on eitherPatreon ($5 donation) orSpotify ($2.99 donation).
Your donation goes directly to supporting this channel and the human labor that goes into each of these episodes. For each episode, we do research and fact-check our content to make sure that you get the best information possible, even on cutting edge topics. Become a Paid Subscriber: https://podcasters.spotify.com/pod/show/data-science-interview/subscribe
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!
The p-value is perhaps one of the most misunderstood topics in analytics and data science! Make sure to stand out by understanding how to truly interpret the results.
If you enjoy our podcast, please consider becoming a premium member on eitherPatreon ($5 donation) orSpotify ($2.99 donation).
Your donation goes directly to supporting this channel and the human labor that goes into each of these episodes. For each episode, we do research and fact-check our content to make sure that you get the best information possible, even on cutting edge topics. Become a Paid Subscriber: https://podcasters.spotify.com/pod/show/data-science-interview/subscribe
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!
Brush up on your knowledge about maximum likelihood estimation, which is important to know in Data Science and Statistics!
If you enjoy our podcast, please consider becoming a premium member on either Patreon ($5 donation) or Spotify ($2.99 donation).
Your donation goes directly to supporting this channel and the human labor that goes into each of these episodes. For each episode, we do research and fact-check our content to make sure that you get the best information possible, even on cutting edge topics. Become a Paid Subscriber: https://podcasters.spotify.com/pod/show/data-science-interview/subscribe
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!
This is our follow up on the previous episode. After this episode, you should be able to understand the difference between a Markov and a Hidden Markov Model at a high-level!
If you enjoy our podcast, please consider becoming a premium member on eitherPatreon ($5 donation) orSpotify ($2.99 donation).
Your donation goes directly to supporting this channel and the human labor that goes into each of these episodes. For each episode, we do research and fact-check our content to make sure that you get the best information possible, even on cutting edge topics. Become a Paid Subscriber: https://podcasters.spotify.com/pod/show/data-science-interview/subscribe
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!
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.
If you enjoy our podcast, please consider becoming a premium member on eitherPatreon ($5 donation) orSpotify ($2.99 donation).
Your donation goes directly to supporting this channel and the human labor that goes into each of these episodes. For each episode, we do research and fact-check our content to make sure that you get the best information possible, even on cutting edge topics. Become a Paid Subscriber: https://podcasters.spotify.com/pod/show/data-science-interview/subscribe
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!
A few weeks ago, we put out a poll to see what you all would like to hear the most. We received the most votes for deep learning and mock interviews, so we put together this shallow mock interview and hope it's helpful for your data science journey. Please let us know if you would like to hear more of this type of content and we will do some research to provide more in-depth mock interviews.
If you would like to support our channel, please do consider becoming a paid subscriber. You would not only get access to all locked episodes, but you would be helping to keep our small channel running! :)
Enjoy this first mock interview and be in the look out for more to come.
Knowing about GANs in deep learning is crucial to understand since they can generate new and realistic data!
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!
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.
Activation functions are an important part of neural networks, so knowing them helps you build smarter models!
Hyperparameter tuning is a must know if you want to understand data science model optimization!
Brush up on your ARIMA and timeseries skills in interviews to prove you're the go-to person for making smart predictions and driving business success!
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.
The Bernoulli Distribution is a must-know in data science interviews! It helps model binary outcomes and pops up a lot in real-world scenarios.
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.
Mastering the binomial distribution for a data science interview equips you the tools you need to solve probability problems!
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!
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!
Basic knowledge of A/B testing is important to know for marketing/product data science roles or analyst interviews. Listen to this episode to refresh on some key concepts!
RNNs have a wide application in NLP and are helpful for understanding sequential data. We offer a very quick and high-level introduction into the world of RNNs in this episode.
The Naïve Bayes Classifier can often come up in data science interviews. Be sure to brush up on this model if you're interested in classification! If you're enjoying our podcast, please consider rating us or joining our paid membership. Thank you and happy modelling!
If you're planning to interview with any team that does A/B testing or statistics, learning about parametric vs. non-parametric is certainly good to know! If you find our podcasts helpful, please consider subscribing to our channel or becoming paid member to support our growth.
Word2Vec is a must-know if you're interested in Natural Language Processing (NLP) or preparing for any entry-level NLP roles. If you find our episodes helpful, we would really appreciate if you would consider becoming a paid member of our channel to support our growth.
Random forests are a versatile algorithm that can handle both regression and classification problems, and can also provide insights into feature importance. Be sure to brush up on the high-level concepts in case you run across them in your work, school, or even in an interview!
ROC-AUC (Receiver Operating Characteristic Area Under the Curve) is an important metric in machine learning because it measures the quality of a binary classifier's predictions. This is a common topic in data science interviews, so it's helpful to brush up on this concept.
In this episode, we give a high-level overview on neural networks and the math behind them. It's always good to know the basics of deep learning, especially when prepping for a data science interview!
Dimensionality reduction is a commonly asked about topic in Data Science Interviews. We'll go over the high-level reasons for using dimensionality reduction techniques as well as go into detail on PCA.
In this episode, we will provide a high-level overview of how to handle imbalanced data. This concept is fundamental to understanding how to build effective machine learning models, and it is often covered in data science interviews.
In today's episode, we'll be discussing regularization, an important technique used to prevent overfitting in machine learning models. If you find these episodes helpful, please consider supporting us on Patreon at patreon.com/user?u=84843123.
Your support will help us continue to produce these episodes and improve the show. Thanks for listening!
In this episode, we will provide a high-level overview of cross-validation in machine learning. This concept is fundamental to understanding how to build effective machine learning models, and it is often covered in data science interviews.
If you find these episodes helpful, please consider supporting us on Patreon at patreon.com/user?u=84843123.
Your support will help us continue to produce these episodes and improve the show. Thanks for listening!
Feature scaling is important in data science because it can help standardize the range of independent variables or features of a dataset. This can be useful for optimization algorithms used in modeling, as well as for helping to compare the importance of different features. A must know for data science interviews!
If you find these episodes helpful, please consider supporting us on Patreon at patreon.com/user?u=84843123.
Your support will help us continue to produce these episodes and improve the show. Thanks for listening!
In this episode, we will provide a high-level overview of the bias variance tradeoff in machine learning. This concept is fundamental to understanding how to build effective machine learning models, and it is often covered in data science interviews.
If you find these episodes helpful, please consider supporting us on Patreon at patreon.com/user?u=84843123.
Your support will help us continue to produce these episodes and improve the show. Thanks for listening!