Statistics For Machine Learning By Spotle

This Spotle masterclass by industry and academic leaders is for people who want to build careers in machine learning

What you'll learn
Probability
Conditional Probability
Bayes Theorem
Random Variables
Variance And Covariance
Probability Distribution In Python
Measuring Central Tendency
Skewness and Kurtosis
Basic Statistics And Data Visualization Using Python
Missing Data Imputation
Statistical Estimation
Overview Of Artificial Intelligence
Overview Of Machine Learning
Overview Of Data Science
Types Of Machine Learning
Supervised And Unsupervised Machine Learning
Semi-supervised Machine Learning
Reinforcement Learning
Requirements
You will need to have a computer or a mobile handset with an internet connection
Description
Data science, machine learning have become key industry drivers in the global job and opportunity market. And statistics is at the core of data science and machine learning. This course with lectures from industry experts and Ivy League academics will help students, recent graduates and young professionals learn statistics and focus deeper in their data science, machine learning careers ahead.In this course you will learn:ProbabilityConditional probabilityBayes TheoremRandom variablesProbability distributionProbability distribution using Python programming languageMeasuring central tendencyMeasuring skewness and kurtosisBasic statistics and data visualization using pythonStatistical estimationMissing data imputationOverview of artificial intelligence, machine learning and data scienceTypes of machine learningSpotleSpotle is an AI-powered talent network matching you to the relevant career path in real-time. Targeted at the highly mobile millennial and Gen-Z workforce, Spotle provides a dynamic and agile platform to discover career choices matched to your life goals.The AI pulls your professional data, analyses your career goals and automatically finds the right networks, career paths and opportunities for you. Think of it as your AI-enabled assistant working 24/7 to help your career grow. Powered by a mix of NLP, predictive modelling and machine learning Spotle crunches all your professional data in the background and automatically discovers for you the right opportunities, networks and career resources for you. Spotle is focused on students and young professionals in the early stages of their career and we understand how important it is for you to have a solid start. The Spotle Learn platform aggregates learnings and content from top academics and industry practitioners and helps you build your skill through an adaptive learning path.For companies or employers, Spotle uses deep matching to instantly surface the right talents you will want to hire. It simplifies the entire hiring process through AI-powered candidate matching. Your talent pipelining becomes easy as Spotle recommends potential hires based on your hiring goals and lets you engage with passive candidates who are not actively applying to jobs right now. It gives you a periscopic view into campus talents through leaderboards and innovative skill points.Spotle reaches over 20,000 Recruiters and a million plus students and young professionals. The company works with leading campuses and companies to craft the right career matches.

Overview

Section 1: Introduction To Probability

Lecture 1 Introduction, Rules And Conditional Probability

Section 2: Conditional Probability

Lecture 2 Conditional Probability

Lecture 3 Bayes Theorem And Conditional Probability

Section 3: Random Variables And Distribution

Lecture 4 Random Variables And Distribution

Lecture 5 Random Variables Expectations And Variance

Section 4: Probability Distribution In Python

Lecture 6 Explaining Probability Distribution In Python

Section 5: Central Tendency

Lecture 7 Measuring Central Tendency

Section 6: Skewness And Kurtosis

Lecture 8 Measuring Skewness And Kurtosis

Section 7: Basic Statistics And Data Visualization

Lecture 9 Basic Statistics And Data Visualization Using Python

Section 8: Missing Data Imputation

Lecture 10 Missing Data Imputation - Part 1

Lecture 11 Missing Data Imputation - Part 2

Section 9: Statistical Inference

Lecture 12 Statistical Estimation

Section 10: Introduction To AI, Machine Learning And Data Science

Lecture 13 Introduction To Artificial Intelligence

Lecture 14 Introduction To Machine Learning

Lecture 15 Introduction To Data Science

Section 11: Types Of Machine Learning

Lecture 16 Supervised And Unsupervised Learning

Lecture 17 Semi-supervised Machine Learning

Lecture 18 Reinforcement Learning

Anyone who wants to learn probability and statistics,Anyone who wants to start a career in data science, machine learning