Absolutely. Adam Grant hits it on the nail again by letting our values define us rather than the roles we play.
Organizational psychologist at Wharton, #1 NYT bestselling author of HIDDEN POTENTIAL and THINK AGAIN, and host of the TED podcasts WorkLife and Re:Thinking
Hope everyone has had a wonderful week. :) For those looking for a refresher on Bernoulli Distributions, you can enjoy this latest release as part of your weekend treat. #distributions, #DataCamp, #applications, #principles, #DataScience, #Statistics, #Probability https://lnkd.in/g92srf3S
Happy Friday! For those looking for a refresher on Boosting techniques, we have just released a new tutorial for you. https://lnkd.in/g3dZSHDi #DataCamp, #MachineLearning, #Algorithms, #AdaBoost, #Ensembles
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Today, we will begin to explore Vector Multiplication Techniques. Take a look at "How to Perform Vector Hadamard Multiplication in Python" when you have a free moment. https://lnkd.in/g83me-m4 #Vectors, #NLP, #ML, #LinearAlgebra, #Statology, #LLMs
Today, we touch upon the concept of the "Dot Product". This technique is repeatedly used in many advanced applications. Please take a moment to read about: "How to Compute the Dot Product of Vectors in Python". :) It will be useful when we discuss "Cosine Distance" soon. https://lnkd.in/gBuG3k-E #LinearAlgebra, #Statology, #Vectors, #Math, #DataScience, #Python #HowTo, #MachineLearningMastery, #NLP
Let's keep chipping away at our daily dose of Linear Algebra. Today, we will look at "How to Multiply a Vector by a Scalar in Python". Keep in mind that we are building towards "Cosine Distance" from our earlier long form post on "Manhattan Distance". Each step will strengthen your foundation. :) https://lnkd.in/g3J3-TDM #LinearAlgebra, #Statology, #Vectors, #Math, #DataScience, #Python, #HowTo, #MachineLearningMastery
