Machine Learning Courses

1. Machine Learning A-Z™: Hands-On Python & R In Data Science

Machine Learning A-Z™: Hands-On Python & R In Data Science

Learn to create Machine Learning Algorithms in Python and R from two Data Science experts. Code templates included.
Content:
- Master Machine Learning on Python & R
- Have a great intuition of many Machine Learning models
- Make accurate predictions

2. Python for Data Science and Machine Learning Bootcamp

Python for Data Science and Machine Learning Bootcamp

Learn how to use NumPy, Pandas, Seaborn , Matplotlib , Plotly , Scikit-Learn , Machine Learning, Tensorflow , and more!
Content:
- Use Python for Data Science and Machine Learning
- Use Spark for Big Data Analysis
- Implement Machine Learning Algorithms

3. Machine Learning, Data Science and Deep Learning with Python

Machine Learning, Data Science and Deep Learning with Python

Complete hands-on machine learning tutorial with data science, Tensorflow, artificial intelligence, and neural networks
Content:
- Build artificial neural networks with Tensorflow and Keras
- Classify images
- data
- and sentiments using deep learning
- Make predictions using linear regression
- polynomial regression
- and multivariate regression

4. Data Science and Machine Learning Bootcamp with R

Data Science and Machine Learning Bootcamp with R

Learn how to use the R programming language for data science and machine learning and data visualization!
Content:
- Program in R
- Use R for Data Analysis
- Create Data Visualizations

5. Introduction to Machine Learning for Data Science

Introduction to Machine Learning for Data Science

A primer on Machine Learning for Data Science. Revealed for everyday people, by the Backyard Data Scientist.
Content:
- Genuinely understand what Computer Science
- Algorithms
- Programming
- Data
- Big Data
- Artificial Intelligence
- Machine Learning
- and Data Science is.
- To understand how these different domains fit together
- how they are different
- and how to avoid the marketing fluff.
- The Impacts Machine Learning and Data Science is having on society.

6. Deep Learning Prerequisites: Linear Regression in Python

Deep Learning Prerequisites: Linear Regression in Python

Data science, machine learning, and artificial intelligence in Python for students and professionals
Content:
- Derive and solve a linear regression model
- and apply it appropriately to data science problems
- Program your own version of a linear regression model in Python

7. Bayesian Machine Learning in Python: A/B Testing

Bayesian Machine Learning in Python: A/B Testing

Data Science, Machine Learning, and Data Analytics Techniques for Marketing, Digital Media, Online Advertising, and More
Content:
- Use adaptive algorithms to improve A/B testing performance
- Understand the difference between Bayesian and frequentist statistics
- Apply Bayesian methods to A/B testing

8. Scala and Spark for Big Data and Machine Learning

Scala and Spark for Big Data and Machine Learning

Learn the latest Big Data technology - Spark and Scala, including Spark 2.0 DataFrames!
Content:
- Use Scala for Programming
- Use Spark 2.0 DataFrames to read and manipulate data
- Use Spark to Process Large Datasets

9. DP-100: A-Z Machine Learning using Azure Machine Learning

DP-100: A-Z Machine Learning using Azure Machine Learning

Microsoft Azure DP-100: Designing and Implementing a Data Science Solution Exam Covered. Learn Azure Machine Learning
Content:
- Prepare for and Pass the Azure DP-100 Exam
- Master Data Science and Machine Learning Models using Azure ML.
- Data Processing using Python and Pandas

10. The Complete Machine Learning Course with Python

The Complete Machine Learning Course with Python

Build a Portfolio of 12 Machine Learning Projects with Python, SVM, Regression, Unsupervised Machine Learning & More!
Content:
- Machine Learning Engineers earn on average $166
- 000 - become an ideal candidate with this course!
- Solve any problem in your business
- job or personal life with powerful Machine Learning models
- Train machine learning algorithms to predict house prices
- identify handwriting
- detect cancer cells & more

11. Machine Learning & Deep Learning in Python & R

Machine Learning & Deep Learning in Python & R

Covers Regression, Decision Trees, SVM, Neural Networks, CNN, Time Series Forecasting and more using both Python & R
Content:
- Learn how to solve real life problem using the Machine learning techniques
- Machine Learning models such as Linear Regression
- Logistic Regression
- KNN etc.
- Advanced Machine Learning models such as Decision trees
- XGBoost
- Random Forest
- SVM etc.

12. AWS Certified Machine Learning Specialty (MLS-C01)

AWS Certified Machine Learning Specialty (MLS-C01)

Hands on AWS ML SageMaker Course with Practice Test. Join Live Study Group Q&A!
Content:
- You will gain first-hand experience on how to train
- optimize
- deploy
- and integrate ML in AWS cloud
- AWS Built-in algorithms
- Bring Your Own
- Ready-to-use AI capabilities
- Complete Guide to AWS Certified Machine Learning – Specialty (MLS-C01)

13. Machine Learning with Javascript

Machine Learning with Javascript

Master Machine Learning from scratch using Javascript and TensorflowJS with hands-on projects.
Content:
- Assemble machine learning algorithms from scratch!
- Build interesting applications using Javascript and ML techniques
- Understand how ML works without relying on mysterious libraries

14. An Introduction to Machine Learning for Data Engineers

An Introduction to Machine Learning for Data Engineers

A Prerequisite for Tensorflow on Google's Cloud Platform for Data Engineers
Content:
- You'll be familiar with many of the basic algorithms used in machine learning.
- You'll have solid understanding of how real world models are built using Python.
- You'll know exactly what machine learning is and what it isn't.

15. Machine Learning Practical: 6 Real-World Applications

Machine Learning Practical: 6 Real-World Applications

Machine Learning - Get Your Hands Dirty by Solving Real Industry Challenges with Python
Content:
- You will know how real data science project looks like
- You will be able to include these Case Studies in your resume
- You will be able better market yourself as a Machine Learning Practioneer

16. Feature Engineering for Machine Learning

Feature Engineering for Machine Learning

Transform the variables in your data and build better performing machine learning models
Content:
- Learn multiple techniques for missing data imputation
- Transform categorical variables into numbers while capturing meaningful information
- Learn how to deal with infrequent
- rare and unseen categories