Probability and Statistics for Machine Learning and Data Science

Colleagues, in the “Probability and Statistics for Machine Learning and Data Science” program you will learn to: Describe and quantify the uncertainty inherent in predictions made by machine learning models; understand the properties of commonly used probability distributions in machine learning and data science, apply common statistical methods like maximum likelihood estimation (MLE) and maximum a priori estimation (MAP) to machine learning problems, and assess the performance of machine learning models using interval estimates and margin of errors. And you will acquire high-demand skills in Statistical Hypothesis Testing, Methods, Inference, Exploratory Data Analysis, Descriptive Statistics, Histogram, Probability Distribution, Correlation Analysis, Statistical Analysis, Data Science, Probability, Box Plots, Sampling (Statistics), Probability and Statistics, Statistical Machine Learning, Bayesian Statistics, Statistical Visualization, and A/B Testing. Describe and quantify the uncertainty inherent in predictions made by machine learning models, using the concepts of probability, random variables, and probability distributions. Visually and intuitively understand the properties of commonly used probability distributions in machine learning and data science like Bernoulli, Binomial, and Gaussian distributions. Apply common statistical methods like maximum likelihood estimation (MLE) and maximum a priori estimation (MAP) to machine learning problems. Assess the performance of machine learning models using interval estimates and margin of errors. Apply concepts of statistical hypothesis testing to commonly used tests in data science like AB testing, and Perform Exploratory Data Analysis on a dataset to find, validate, and quantify patterns. Training lessons encompass: 1) Introduction to Probability and Probability Distributions, 2) Describing Probability Distributions, 3) Sampling and Point Distributions, 4) Confidence Intervals and Hypothesis Testing.

Enroll today!: Teams and executives are welcome: https://imp.i384100.net/QY6mM6

Listen today via Amazon Audible (https://tinyurl.com/ydbyh2t9) 

Or read now on Kindle (https://tinyurl.com/hptundzs) 

These books are part of the “Data-Driven Organizations” series.

1 - The Promise of Data-Driven Decision-Making  (Audible) (Kindle)

2 - Implementing Data Science Methodology: From Data Wrangling to Data Viz (Audible) (Kindle)

3 - “The Upskill Gambit - Discover the 5 Keys to Your Career and Income Security in the Digital Age” (Audible) (Kindle)

Much career success from the Data Science Academy (please subscribe and share with your colleagues)