Data Science career advice, future trends, and LinkedIn Top Voice Vin Vashishta

Data Transformers Podcast Data Science career advice, future trends, and LinkedIn Top Voice Vin Vashishta 1x 00:00 / 00:30:09 Subscribe Share Apple Podcasts Google Podcasts Spotify Stitcher TuneIn RSS Feed Share Link Embed

Data Science career advice, future trends, and LinkedIn Top Voice Vin Vashishta

' /> Apple Podcasts Google Podcasts Spotify Stitcher https://youtu.be/u-Dy5F0lBS0 Episode Title: Data Science career advice, future trends, and LinkedIn Top Voice Vin Vashishta Episode Summary: Career advice in data science is one area of Vin Vashishta’s many published articles that got a lot of attention. Vin talked about the gap between job descriptions and actual hiring. The episode also focused on future trends and especially on adversarial machine learning that Vin Vashishta believes will be important. Vin also talked about the impact of being recognized as LinkedIn Top Voice. Topics discussed in this episode: Job description Vs. who gets hired (02:00): Job description is typically a recommendation and is poorly built. There is a gap between what the description says, who gets interviewed and who gets hired. A hiring manager will be looking for capabilities of what you can make and what you can build versus just knowledge. So the advice to job aspirants is to show capabilities and not jus knowledge. Vin’s evolution into research into career advice (08:26): Vin mentioned that what he works on now is not what he gets used now. So his research on careers was from few years ago and getting more attention now. Another example is his research into adversarial intelligence which he believes will be commonplace discussion in a few years. Future trends in AI & ML (13:38): Vin believes that adversarial machine learning or cybersecurity for AI models will be a huge topic in a couple of years. The hackers will try to inject ‘poison’ into models along with data. Or it could happen with a couple of machine learning models ‘talking’ to each other. It may even be difficult to figure out the differences between ‘collaborative’ versus ‘adversarial’ approach. Inequality between companies because of AI (19:55): The concept of ‘business dynamism’ where the forerunners, like Google & Facebook,  are consolidating capabilities and IP and this consolidated IP is not tricked to other companies. So companies, especially the laggard ones, need to understand their core capabilities if they want to stay relevant. What it means to be LinkedIn’s Top Voice (25:30): The Top Voice recognition definitely helped Vin extend his visibility and impact. With respect to business, Vin said what he writes about and what hoe does for a living are two separate things. So the Top Voice may not have contributed much to his business. Resources mentioned in this episode: The ML Rebellion blog: https://themlrebellion.com/ Data By V-Squared: https://databyvsquared.com/  Call to action: Connect with Vin Vashishta: https://www.linkedin.com/in/vineetvashishta/  Follow Data Transformers on Twitter: @DataTransforme2  Listen to other Data Transformer episodes and Rate the episodes: Data Transformers Podcast

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