
Sign up to save your podcasts
Or


Richmond Alake, a Machine Learning Architect at Slalom Build, sits down with Jon to share real-time ML insights, tools and career experiences for a high-energy and high impact episode. From his work at Slalom Build to his two AI startups, discover the software choices, ML tools, and front-end development techniques used by a leader in the field.
This episode is brought to you by Posit, the open-source data science company, by AWS Inferentia, and by WithFeeling.ai, the company bringing humanity into AI. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.
In this episode you will learn:
• What is a Machine Learning Architect? [03:09]
• Richmond's startups [12:07]
• Why Richmond started a podcast [29:51]
• Richmond's new course on feature stores [38:05]
• Why Richmond produces data science content [43:25]
• Why All Data Scientists Should Write [51:30]
Additional materials: www.superdatascience.com/685
By Jon Krohn4.6
294294 ratings
Richmond Alake, a Machine Learning Architect at Slalom Build, sits down with Jon to share real-time ML insights, tools and career experiences for a high-energy and high impact episode. From his work at Slalom Build to his two AI startups, discover the software choices, ML tools, and front-end development techniques used by a leader in the field.
This episode is brought to you by Posit, the open-source data science company, by AWS Inferentia, and by WithFeeling.ai, the company bringing humanity into AI. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.
In this episode you will learn:
• What is a Machine Learning Architect? [03:09]
• Richmond's startups [12:07]
• Why Richmond started a podcast [29:51]
• Richmond's new course on feature stores [38:05]
• Why Richmond produces data science content [43:25]
• Why All Data Scientists Should Write [51:30]
Additional materials: www.superdatascience.com/685

475 Listeners

1,086 Listeners

339 Listeners

769 Listeners

156 Listeners

268 Listeners

209 Listeners

141 Listeners

90 Listeners

131 Listeners

150 Listeners

208 Listeners

559 Listeners

266 Listeners

70 Listeners