Pull over machine operator education requirements

1. Support Vector Machine Classification in Python

In this 1-hour long guided project-based course, you will learn how to use Python to implement a Support Vector Machine algorithm for classification. This type of algorithm classifies output data and makes predictions. The output of this model is a set of visualized scattered plots separated with a straight line. You will learn the fundamental theory and practical illustrations behind Support Vector Machines and learn to fit, examine, and utilize supervised Classification models using SVM to...

2. Machine Learning with PySpark: Customer Churn Analysis

This 90-minute guided-project, "Pyspark for Data Science: Customer Churn Prediction," is a comprehensive guided-project that teaches you how to use PySpark to build a machine learning model for predicting customer churn in a Telecommunications company. This guided-project covers a range of essential tasks, including data loading, exploratory data analysis, data preprocessing, feature preparation, model training, evaluation, and deployment, all using Pyspark. We are going to use our machine...

3. Data Science: Complete Data Science & Machine Learning

4.6

(2,869)

Learn and master the Data Science, Python for Machine Learning, Math for Machine Learning, Statistics for Data Science...

4. Azure Machine Learning & MLOps: Beginner to Advance

4.4

(465)

The most compressive course covering MLOps and machine learning on Azure Zero to Hero...

5. Build your first Machine Learning Pipeline using Dataiku

As part of this guided project, you shall build your first Machine Learning Pipeline using DataIku tool without writing a single line of code. You shall build a prediction model which inputs COVID daily count data across the world and predict COVID fatalities.DataIku tool is a low code no code platform which is gaining traction with citizen data scientist to quickly build and deploy their models...

6. Truck Dispatcher - Working with owner operators

4.6

(724)

Work and earn...

7. Machine Learning No-Code Approach: Using Azure ML Studio

4.9

(542)

A hands-on approach to Machine Learning using the easy drag-n-drop environment of Azure Machine Learning Studio...

8. Productivity Machine: Time Management & Productivity Hacks

4.5

(27,996)

Productivity & Time Management Strategies for Goal Setting, Eliminating Distractions, & Building Habits for Success...

9. Azure Machine Learning using Cognitive Services

4.8

(433)

Learn the Azure Machine Learning Studio, Azure Bot Service, Video Indexing service, Computer Vision for OCR and more!...

10. Projects in Machine Learning: Beginner To Professional

4.3

(591)

A complete guide to master machine learning concepts and create real world ML solutions...

11. Machine Learning Practical Workout 8 Real-World Projects

4.6

(1,590)

Build 8 Practical Projects and Go from Zero to Hero in Deep/Machine Learning, Artificial Neural Networks...

12. 5 Machine Learning Projects from Dataisgood / Great Reviews

4

(711)

Learn Complete Machine Learning Bootcamp with Python. Build 5 Complete Machine Learning Real World Projects with Python...

13. Machine Learning for Data Analysis: Classification Modeling

4.7

(439)

Machine Learning made simple with Excel! Classification for advanced data analysis & business intelligence (no coding!)...

14. Mathematical Foundation For Machine Learning and AI

4.6

(1,262)

Learn the core mathematical concepts for machine learning and learn to implement them in R and python...

15. Machine Learning - Regression and Classification (math Inc.)

4.5

(477)

A complete Beginner to Advance level guide to Machine Learning. Hands-on Learning approach with in-depth math concepts...

16. Mastering Data Science and Machine Learning Fundamentals

4.6

(1,396)

Data Science & Machine Learning- Data Science, Machine Learning, Regression, Classification and Clustering [THEORY ONLY]...

17. Support Vector Machines in Python: SVM Concepts & Code

4.6

(497)

Learn Support Vector Machines in Python. Covers basic SVM models to Kernel-based advanced SVM models of Machine Learning...

18. Complete Machine Learning & Data Science with Python ML A-Z

4.6

(456)

Learn Numpy, Pandas, Matplotlib, Seaborn, Scipy, Supervised & Unsupervised Machine Learning A-Z and feature engineering...

19. Machine Learning: Natural Language Processing in Python (V2)

4.8

(3,559)

NLP: Use Markov Models, NLTK, Artificial Intelligence, Deep Learning, Machine Learning, and Data Science in Python...