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Description

We get lost in the details. Always find ourselves not knowing where to begin or where we are heading... Lets take a bird's view on things. So we would have a better idea on how to get to where we want. This podcast is a bird's eye view on all things machine learning. Explained to people in a hurry. ( You and me :)

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Check latest episodes from Machine Learning Teeta podcast

Bias and variance

2022/04/21

Simply, what are the bias and variance? Why is there a tradeoff between them? Listen to this episode to learn about this fundamental topic which is usually asked about during data science and machine learning job interviews.

Design Of Experiments in less than 30 minutes

2022/03/24

What is design of experiments? Student t-test? ANOVA? These are really simple to explain. Listen to this episode to learn about them.

Hardware for deep learning, sequel

2021/05/21

What hardware do I need to run ML deep learning models? For prototyping.

Hardware for deep learning

2021/05/21

How is the computationally intensive deep learning accomplished on modern hardware computers ? A basic introduction.

Topic modeling (2); evaluation metrics

2021/05/06

How can we compare one topic model to another? How can we evaluate any one of them?

Non linear classifiers; decision trees intro

2021/05/03

Now is time to discuss non linear classifiers, which provide flexibility in modeling more complex patterns in data. We start by a conceptual intro to decision trees in this short episode

Machine learning - Bayes decision theory

2021/04/24

The bird's eye view on classifiers. In this episode, we walk thru the landscape and start with linear classifiers. In the next episode, we will go thru non-linear classifiers isA.

Data analysis process

2021/04/04

We describe the 5 steps of data analysis. Speak of common steps and the pitfalls.

Topic modeling part 1

2021/03/06

Topic modelling part 1, LSA

NLP systems.

2021/02/26

How do you build a NLP systems? What are the system level parameters you should consider ? How to choose one algorithm over another? And how to evaluate NLP systems. This episode is about answering these questions.

Machine Learning Teeta (Trailer)

2021/02/25