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Brush up on your knowledge about maximum likelihood estimation, which is important to know in Data Science and Statistics!
Become a Paid Subscriber for access to our full library: https://podcasters.spotify.com/pod/show/data-science-interview/subscribe
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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!
By Data Science Interview Prep Podcast5
1616 ratings
Brush up on your knowledge about maximum likelihood estimation, which is important to know in Data Science and Statistics!
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 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!

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