80 min listen
From Physics to Machine Learning - Tatiana Gabruseva
FromDataTalks.Club
ratings:
Length:
67 minutes
Released:
May 14, 2021
Format:
Podcast episode
Description
We talked about:
Tatiana’s background
12 career hacks and changing career
Hack #1: Change your social circle
Hack #2: Forget your fears and stereotypes
Hack #3: Forget distractions
Hack #4: Don’t overestimate others and don’t underestimate yourself
Hack #5: Attention genius
Hack #6: Make a team
Hack #7: Less is more. Forget about perfectionism
Hack #8: Initial creation
Hack #9: Find mentors
Hack #10: Say “no”
Hack #11: Look for failures
Hack #12: Take care of yourself
Kaggle vs internships and pet projects
Resources for learning machine learning
Starting with Kaggle
Improving focus
Astroinformatics
How background in Physics is helpful for transitioning
Leaving academia
Preparing for interviews
Links:
Mock interviews: https://www.pramp.com/
Learning ML: https://www.coursera.org/learn/machine-learning and https://www.coursera.org/specializations/deep-learning
Python: https://www.coursera.org/learn/machine-learning-with-python
SQL: https://www.sqlhabit.com/
Practice: https://www.kaggle.com/
MIT 6.006: https://courses.csail.mit.edu/6.006/fall11/notes.shtml
Coding: https://leetcode.com/
System design: https://www.educative.io/courses/grokking-the-system-design-interview
Ukrainian telegram groups for interview preparation: https://t.me/FaangInterviewChannel, https://t.me/FaangTechInterview, https://t.me/FloodInterview
Join DataTalks.Club: https://datatalks.club/slack.html
Tatiana’s background
12 career hacks and changing career
Hack #1: Change your social circle
Hack #2: Forget your fears and stereotypes
Hack #3: Forget distractions
Hack #4: Don’t overestimate others and don’t underestimate yourself
Hack #5: Attention genius
Hack #6: Make a team
Hack #7: Less is more. Forget about perfectionism
Hack #8: Initial creation
Hack #9: Find mentors
Hack #10: Say “no”
Hack #11: Look for failures
Hack #12: Take care of yourself
Kaggle vs internships and pet projects
Resources for learning machine learning
Starting with Kaggle
Improving focus
Astroinformatics
How background in Physics is helpful for transitioning
Leaving academia
Preparing for interviews
Links:
Mock interviews: https://www.pramp.com/
Learning ML: https://www.coursera.org/learn/machine-learning and https://www.coursera.org/specializations/deep-learning
Python: https://www.coursera.org/learn/machine-learning-with-python
SQL: https://www.sqlhabit.com/
Practice: https://www.kaggle.com/
MIT 6.006: https://courses.csail.mit.edu/6.006/fall11/notes.shtml
Coding: https://leetcode.com/
System design: https://www.educative.io/courses/grokking-the-system-design-interview
Ukrainian telegram groups for interview preparation: https://t.me/FaangInterviewChannel, https://t.me/FaangTechInterview, https://t.me/FloodInterview
Join DataTalks.Club: https://datatalks.club/slack.html
Released:
May 14, 2021
Format:
Podcast episode
Titles in the series (100)
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