Machine Learning Interview Help (Hindi)

Mr. Hulk
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"Machine Learning Interview Help" is a podcast designed to assist candidates who are preparing for machine learning or deep learning interviews. In this podcast, I will cover various machine learning algorithms, and explain the types of questions typically asked by interviewers during interviews for machine learning or related positions. I will explore each topic in-depth and help you understand what the interviewer is looking for based on the job description. I will also break down the math behind various machine learning topics and explain it in a way that is easy to understand.

  1. 2023/03/24

    E15 - Normalization vs Standardization

    This episode discusses the difference between Normalization and Standardization. I have also discussed which method we should use based on the use case and ML algorithms. If you have not listened to the episodes on mean standard deviation and variance, then please listen to them first. Link to my website to check out the formulas.

    10 分鐘

  2. 2023/03/15

    E14 - Regularization Interview Questions

    This episode discusses the interview questions based on the topic of Regularization in machine learning. The Link to my website ---->  Link

    6 分鐘
  3. E13 - Regularization Concept Understanding

    2023/02/20

    E13 - Regularization Concept Understanding

    In this episode, I explained the concept of regularization in layman's language to develop a clear understanding of it and its relation with bias and variance. It is recommended to listen to the previous episode (Bias and Variance) first.

    10 分鐘
  4. E12 - Bias and Variance

    2023/02/13

    E12 - Bias and Variance

    Welcome to our latest episode.  Today, we are going to discuss one of the most fundamental concepts in machine learning - Bias and Variance. Understanding the concept of bias and variance is crucial for developing effective machine learning models. These two parameters help us to measure the accuracy of our predictions and understand how to improve our models. We will explain these concepts in detail and show how to balance them for optimal results. So, sit back, relax, and get ready to learn about one of the most important topics in machine learning

    13 分鐘
  5. E11 - How to control the interview

    2023/02/10

    E11 - How to control the interview

    Interviewing for a job in the machine learning field can be nerve-wracking, especially when it comes to technical questions. But what if I told you that you have the power to steer the interview in a direction that plays to your strengths? In this episode, we're diving into the tips and tricks for controlling the interview and showcasing your knowledge to potential employers. मशीन लर्निंग क्षेत्र में नौकरी के लिए साक्षात्कार नर्व-ब्रेकिंग हो सकता है, खासकर जब तकनीकी प्रश्नों की बात आती है। लेकिन क्या होगा अगर मैंने आपको बताया कि आपके पास साक्षात्कार को उस दिशा में ले जाने की शक्ति है|   इस कड़ी में, हम साक्षात्कार को नियंत्रित करने और संभावित नियोक्ताओं को अपना ज्ञान प्रदर्शित करने के लिए टिप्स और ट्रिक्स के बारे में बात करेंगे।

    10 分鐘
  6. E10 - Linear Algebra Part 2

    2022/09/05

    E10 - Linear Algebra Part 2

    This episode discusses the orthogonal and orthonormal properties of vectors

    11 分鐘
  7. E9 - Linear Algebra Part 1

    2022/08/26

    E9 - Linear Algebra Part 1

    This episode brings you a glimpse of vectors, vector space, basis, and dimensionality of a vector space. Enjoy !!!!!

    13 分鐘

  8. 2022/05/27

    E8 - Histogram and Probability Distribution

    This episode explains the concept behind the Histogram and Probability distribution along with the comparison between them. Please use this Link to check the example plot of histogram and probability distribution.

    19 分鐘
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簡介

"Machine Learning Interview Help" is a podcast designed to assist candidates who are preparing for machine learning or deep learning interviews. In this podcast, I will cover various machine learning algorithms, and explain the types of questions typically asked by interviewers during interviews for machine learning or related positions. I will explore each topic in-depth and help you understand what the interviewer is looking for based on the job description. I will also break down the math behind various machine learning topics and explain it in a way that is easy to understand.

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