Home AI Courses Probability & Statistics for Machine Learning & Data Science

Probability & Statistics for Machine Learning & Data Science

(0 reviews)

Understand and apply statistical techniques to quantify prediction uncertainty, analyze probability distributions, and evaluate machine learning model efficacy using interval estimates and margins of error.

Key AI Functions:Probability And Statistics,Machine Learning (ML) Algorithms,Statistical Analysis,Probability,Statistical Hypothesis Testing

Description

Reviews

Alternative Tools

Description for Probability & Statistics for Machine Learning & Data Science

Features of Course

Quantify and describe the inherent uncertainty in the predictions produced by machine learning models.

Visually and intuitively comprehend the characteristics of probability distributions that are frequently employed in the fields of data science and machine learning.

Utilize conventional statistical techniques, including maximum likelihood estimation (MLE) and maximum a priori estimation (MAP), to address machine learning issues.

Evaluate the efficacy of machine learning models by utilizing interval estimates and margin of errors.

Level: Beginner

Certification Degree: Yes

Languages the Course is Available: 22

Offered by: On Coursera provided by DeepLearning.AI

Duration: 33 hours (approximately)

Schedule: Flexible

Reviews for Probability & Statistics for Machine Learning & Data Science

0 / 5

from 0 reviews

Ease of Use

Ease of Customization

Intuitive Interface

Value for Money

Support Team Responsiveness

Featured Tools

Intro to Vertex AI Studio

DeepLearning.AI TensorFlow Developer Professional Certificate

Gen AI GPT Vision

Statistical Learning for Data Science Specialization

Managing ML Projects

Alternative Tools for Probability & Statistics for Machine Learning & Data Science

AI and ML Essentials with Python Specialization

Investigate the field of artificial intelligence and machine learning. While investigating the transformative disciplines of artificial intelligence, machine learning, and deep learning, enhance your Python abilities.

#Artificial Intelligence #Python (Programming Language)

IBM Machine Learning Professional Certificate

Set up for a profession in machine learning. To become job-ready in less than three months, acquire the skills and practical experience that are in high demand.

#Statistical Hypothesis Testing #Machine Learning (ML) Algorithms

Mathematics for ML & Data Science Specialization

Master the AI and machine learning toolkit. Mathematics for Machine Learning and Data Science is a Specialization that is accessible to beginners. In this program, you will acquire the basic mathematics tools of machine learning, including calculus, linear algebra, statistics, and probability.

#Bayesian Statistics #Mathematics

Google Advanced Data Analytics Professional Certificate

In less than six months, acquire skills that are in high demand, including machine learning, regression models, Python, and statistical analysis.

#Data Science #Data Analysis

ML : Algorithms in the Real World Specialization

Real-World Applications of Machine Learning. Develop proficiency in the implementation of a machine learning undertaking.

#Project Management #Machine Learning (ML) Algorithms

Practical Machine Learning

Learn to construct and implement prediction functions, understand overfitting and error rates, and grasp machine learning techniques like classification trees and regression.

#Random Forest #Machine Learning (ML) Algorithms

Supervised ML: Classification

This course teaches aspiring data scientists to train and compare classification models using supervised machine learning techniques, focusing on practical applications and best practices.

#Ensemble Learning #Machine Learning (ML) Algorithms

An Intuitive Intro to Probability

Gain essential skills in Probability Theory for managing uncertainty, structured into five modules with practical exercises, covering topics like Probability, Conditional Probability, and offering an engaging online learning experience.

#Bayes' Theorem #Normal Distribution

CertNexus Certified AI Practitioner Professional Certificate

Become an expert in the field of artificial intelligence. Develop effective strategies for the application of Artificial Intelligence techniques to address business challenges.

#Linear Regression #Machine Learning (ML) Algorithms

Featured Tools

Intro to Vertex AI Studio

Utilizing Vertex AI Studio for model management, integrating with Gemini multimodal capabilities, employing effective prompts, and optimizing models through tuning methods are all topics addressed on the course page.

#Vertex AI #Gemini

DeepLearning.AI TensorFlow Developer Professional Certificate

Learn to use TensorFlow for computer vision and natural language processing, manage image data, prevent overfitting, and train RNNs, GRUs, and LSTMs on text repositories.

#Computer Vision #Convolutional Neural Network

Gen AI GPT Vision

Explore the use of generative AI tools to enhance data preparation, querying, and machine learning model development in data science workflows through hands-on projects.

#Prompt Engineering #Generative AI

Statistical Learning for Data Science Specialization

Mastering Advanced Statistics for Data Science. Acquire the necessary knowledge and abilities to effectively communicate the choices and interpretations of models.

#Unsupervised Learning #Resampling

Managing ML Projects

This second course in Duke University's AI Product Management Specialization delves into the practical aspects of managing machine learning projects, such as the identification of opportunities, the application of data science processes, the making of critical technological decisions, and the implementation of best practices from concept to production.

#Modeling #Project Management

Compare & Review AI Tool Directory AI Course Marketplace