Artwork

Sanket Gupta에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Sanket Gupta 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
Player FM -팟 캐스트 앱
Player FM 앱으로 오프라인으로 전환하세요!

6 Steps to Transition to Data Science from non-CS background

15:58
 
공유
 

Manage episode 243278353 series 2550866
Sanket Gupta에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Sanket Gupta 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

In this episode we will talk all about the various steps to transition to data science from non computer science backgrounds.
One of the main difficulties people face from non-CS backgrounds is how overwhelming it can be to transition to data science field, I talk about my own journey, and share the 6 steps which can help you in your own data science career!

00:00 to 02:10: Introduction

02:11 to 06:00: My Background of moving to data science from electrical engineering

06:01 to 10:56: Steps 1 to 3 covering things like using external APIs, already processed datasets and performing full stack data science work

10:57 to 11:55: Break sponsored by Anchor

11:56: End: Steps 4 to 6 covering things like math and statistics, machine learning pipelines and data structures & algorithms

Some useful links:

1) Andrew Ng Deep Learning Specialization Coursera https://www.coursera.org/specializations/deep-learning

2) Intro to Statistics by Sebastien Thrun https://www.udacity.com/course/intro-to-statistics--st101

3) Aurelion Geron's book on machine learning https://www.amazon.com/dp/1491962291/?tag=omnilence-20

4) Pramp for mock algorithm sessions on video https://www.pramp.com/

5) Leetcode for algorithm question datasets https://leetcode.com/

Some great datasets to get started in machine learning:

6) MNIST for hand written digits https://www.kaggle.com/c/digit-recognizer

7) Iris dataset for flower classification http://archive.ics.uci.edu/ml/datasets/iris

8) IMDB movie reviews https://ai.stanford.edu/~amaas/data/sentiment/

Thanks for listening!

--- Send in a voice message: https://podcasters.spotify.com/pod/show/the-data-life-podcast/message Support this podcast: https://podcasters.spotify.com/pod/show/the-data-life-podcast/support

  continue reading

27 에피소드

Artwork
icon공유
 
Manage episode 243278353 series 2550866
Sanket Gupta에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Sanket Gupta 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

In this episode we will talk all about the various steps to transition to data science from non computer science backgrounds.
One of the main difficulties people face from non-CS backgrounds is how overwhelming it can be to transition to data science field, I talk about my own journey, and share the 6 steps which can help you in your own data science career!

00:00 to 02:10: Introduction

02:11 to 06:00: My Background of moving to data science from electrical engineering

06:01 to 10:56: Steps 1 to 3 covering things like using external APIs, already processed datasets and performing full stack data science work

10:57 to 11:55: Break sponsored by Anchor

11:56: End: Steps 4 to 6 covering things like math and statistics, machine learning pipelines and data structures & algorithms

Some useful links:

1) Andrew Ng Deep Learning Specialization Coursera https://www.coursera.org/specializations/deep-learning

2) Intro to Statistics by Sebastien Thrun https://www.udacity.com/course/intro-to-statistics--st101

3) Aurelion Geron's book on machine learning https://www.amazon.com/dp/1491962291/?tag=omnilence-20

4) Pramp for mock algorithm sessions on video https://www.pramp.com/

5) Leetcode for algorithm question datasets https://leetcode.com/

Some great datasets to get started in machine learning:

6) MNIST for hand written digits https://www.kaggle.com/c/digit-recognizer

7) Iris dataset for flower classification http://archive.ics.uci.edu/ml/datasets/iris

8) IMDB movie reviews https://ai.stanford.edu/~amaas/data/sentiment/

Thanks for listening!

--- Send in a voice message: https://podcasters.spotify.com/pod/show/the-data-life-podcast/message Support this podcast: https://podcasters.spotify.com/pod/show/the-data-life-podcast/support

  continue reading

27 에피소드

모든 에피소드

×
 
Loading …

플레이어 FM에 오신것을 환영합니다!

플레이어 FM은 웹에서 고품질 팟캐스트를 검색하여 지금 바로 즐길 수 있도록 합니다. 최고의 팟캐스트 앱이며 Android, iPhone 및 웹에서도 작동합니다. 장치 간 구독 동기화를 위해 가입하세요.

 

빠른 참조 가이드