Created by Lazy Programmer Inc., Lazy Programmer Team 13.5 hours on-demand video course This Math 0-1: Calculus for Data Science & Machine Learning course will cover Calculus 1 (limits, derivatives, and the most important derivative rules), Calculus 2 (integration), and Calculus 3 (vector calculus). It will even include machine learning-focused material you wouldn't normally see in a regular college course. We will even demonstrate many of the concepts in this course using the Python programming language (don't worry, you don't need to know Python for this course). In other words, instead of the dry old college version of calculus, this Math 0-1: Calculus for Data Science & Machine Learning course takes just the most practical and impactful topics, and provides you with skills directly applicable to machine learning and data science, so you can start applying them today.

Free Applied Machine Learning, Data Science, Data Analytics, Programming Language Tutorials and Math Worksheets

Why should you take this course? Naive Bayes is one of the fundamental algorithms in machine learning, data science, and artificial intelligence. No practitioner is complete without mastering it. This course is designed to be appropriate for all levels of students, whether you are beginner, intermediate, or advanced. You'll learn both the intuition for how Naive Bayes works and how to apply it effectively while accounting for the unique characteristics of the Naive Bayes algorithm.

Python has become the go-to language for data science and machine learning because it offers a wide range of tools for building data pipelines, visualizing data, and creating interactive dashboards that are smart and intuitive.

Are you ready to transition your career into becoming a Data Scientist? This comprehensive course will be your guide to learning how to use the power of Python to analyze data, create beautiful visualizations, and use powerful machine learning algorithms! Data scientist is one of the best suited professions to thrive this century. It is digital, programming-oriented, and analytical. Therefore, it comes as no surprise that the demand for data scientists has been surging in the job marketplace.

The Indian Institute of Technology (IIT), Roorkee is offering a five-month online course on data science and machine learning (ML). The course is conducted by Imarticus Learning in association with iHUB DivyaSampark to enable candidates to leverage data Science and ML for effective decision-making. Prof Sudeb Dasgupta, project director of iHUB DivyaSampark said in a press release, "We bring iHUB DivyaSampark's expertise in building outstanding programs with IITs and Imarticus' technical expertise to deliver an outstanding learning experience through a holistic approach. Together, we envision creating a skilled workforce for innovation and digital growth." For more information, go through the brochure.

Electrification was, without a doubt, the greatest engineering marvel of the 20th century. The electric motor was invented way back in 1821, and the electrical circuit was mathematically analyzed in 1827. But factory electrification, household electrification, and railway electrification all started slowly several decades later. The field of AI was formally founded in 1956. But it's only now--more than six decades later--that AI is expected to revolutionize the way humanity will live and work in the coming decades.

Welcome to the Learn Data Science and Machine Learning with R from A-Z Course! In this practical, hands-on course you'll learn Welcome to the Learn Data Science and Machine Learning with R from A-Z Course! In this practical, hands-on course you'll learn how to program in R and how to use R for effective data analysis, visualization and how to make use of that data in a practical manner. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language. Our main objective is to give you the education not just to understand the ins and outs of the R programming language, but also to learn exactly how to become a professional Data Scientist with R and land your first job.

For the last part of the Statistics series, we will cover the ANOVA, Post-hoc Pairwise Comparison, Two-way ANOVA, and R-squared. Previously, our study focused on one or two groups of subjects. How can we handle the concept of multiple groups with multiple factors? For example, the dose level and gender may impact the effectiveness of a vaccine. How can we determine whether it is statistically significant for particular combinations?

Data Science and Machine Learning are the hottest skills in demand but challenging to learn. Did you wish that there was one course for Data Science and Machine Learning that covers everything from Math for Machine Learning, Advance Statistics for Data Science, Data Processing, Machine Learning A-Z, Deep learning and more? Well, you have come to the right place. This Data Science and Machine Learning course has 11 projects, 250 lectures, more than 25 hours of content, one Kaggle competition project with top 1 percentile score, code templates and various quizzes. Today Data Science and Machine Learning is used in almost all the industries, including automobile, banking, healthcare, media, telecom and others.