What You’ll Discover in Introduction to Machine Learning for Data Science
Introduction to Machine Learning for Data Science
Course Updated Most Recently Nov/2018
Thank you all for The overwhelming response to This is the new course! We are delighted to Over 20,000 students have enrolled in our program from 160 different countries. The overwhelmingly positive and thoughtful comments have truly touched me. It’s a great privilege to Share this important topic with everyday people in an easy to understand way.
Also, I am excited to announcing that I have created closed captions for You can access all course material regardless of whether you have a specific need. to You may have a hearing impairment or it might be easier. to Follow long (great). for ESL students I’ve got you covered.
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But most importantly:
To take this course “real”, we’ve expanded. The course was upgraded to 41 lectures with 8 sections in November 2018. to There are 62 lectures and 15 sections. We hope you enjoy this new content!
Discover the secrets to understanding Machine Learning for Data Science!
This is the introductory course. “Backyard Data Scientist” We will take you through the wilderness Machine Learning for Data Science. Accessible to This introductory course is for everyone. Machine LearningIt is, however, where it belongs in the “techno sphere around us”, why it’s important now, and how it will dramatically change our world today and for Days to come.
This exotic journey will incorporate the core concepts:
The train wreck definition and one that actually makes sense in computer science.
A data explanation that will make you see data everywhere you look
One of the “greatest lies” Ever sold about the future in computer science.
Big: A real explanation DataHow? to Avoid falling for the marketing hype.
Artificial intelligence – What is it? Is it possible for computers to actually think? What is the best way for computers to do tasks like playing games or navigate with a GPS?
What is it? Machine Learning? And if a computer can think – can it learn?
What is it? Data ScienceWhat does it mean? to Magical unicorns
Computers Science, Artificial Intelligence, Machine LearningBig! Data And Data Science Interrelate to Each other.
We’ll then explore the past and the future while touching on the importance, impacts and examples of Machine Learning for Data Science:
What a perfect storm of data and computer and Machine Learning Algorithms have been combined to This is an important moment.
We’ll actually make sense of how computer technology has changed over time while covering off a journey from 1956 to 2014. Are you able to run supercomputers from your own home? You might be surprised to Find out the truth.
We’ll discuss the kinds of problems Machine Learning Visually explains and solves regression, classification, and clustering in a way that makes intuitive sense.
Most importantly we’ll show how this is changing our lives. Not just the lives of business leaders, but most importantly…you too!
To understand the Machine A part of Machine Learning, we’ll explore the Machine Learning process:
How can you solve problems? Machine Learning What are the five essential things to do? to Be successful
How to Ask the right questions to be solved by Machine Learning.
Identifying, obtaining and preparing the right data … and dealing with dirty data!
How each mess looks “unique” But that neat data is like family!
How to Apply and identify Machine Learning algorithm names with exotic names such as “Decision Trees”, “Neural Networks” “K’s Nearest Neighbors” And “Naive Bayesian Classifiers”
The biggest pitfalls to Avoid and How to tune your Machine Learning models to Help ensure a successful outcome for Data Science.
The final section of this course will prepare students. to Begin your next journey! Machine Learning for Data Science Once the course has been completed. We’ll explore:
How to Apply now Machine Learning You can keep your head clear.
What equipment? Data Scientists use (the answer might surprise)
Download immediately Introduction to Machine Learning for Data Science
These are the top five most used tools for Data science, even some unexpected ones.
And for each of the top five tools – we’ll explain what they are, and how to Get started with them.
And we’ll close off with some cautionary tales, so you can be the most successful you can be in applying Machine Learning to Data Science problems.
Bonus Course This is how you make it! “really real”, I’ve included a bonus course!
Most importantly in the bonus course I’ll include information at the end of every section titled “Further Magic to Explore” These will assist you to continue your learning experience.
In this bonus course we’ll explore:
Realizing a life you love Machine Learning Example of Titanic proportions. That’s right – we are going to You can predict your Titanic’s survival!
Anaconda Jupyter can be used with python3.x
A crash course in Python – Covers all the fundamental concepts of Python that you require to These code examples will help you understand the concepts. Check out the cheat sheet that comes with your package!
You will learn how to run Python. Interactively, with scripts, or with Jupyter
How it works to Use Jupyter notebooks
Revision and reinforcement of core concepts Machine Learning (that we’ll soon apply!)
Foundations of essential Machine Learning And Data Science modules:
NumPy – An Array Implementation
Pandas – The Python Data Analysis Library
Matplotlib – A plotting library which produces quality figures in a variety of formats
SciPy – The fundamental Package for Python for scientific computing
Scikit-Learn – Simple and efficient tools data mining, data analysis, and Machine Learning
In the titanic hands on example we’ll follow all the steps of the Machine Learning All aspects of workflow:
1. Asking the right question.
2. Finding, obtaining, and preparing data
3. Recognizing and applying an a Machine Learning algorithm
4. Evaluation of the performance of your model and adjustment
5. Use and presentation of the model
We’ll also see a real world example of problems in Machine Learning, including both underfit and overfit.
The bonus course ends with a conclusion, and additional resources to Continue reading Machine Learning journey.
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So, I invite you to Join me in my Backyard Data Scientists embark on an extraordinary journey to uncover the secrets of Machine Learning for Data Science….. for You know, everyday people …. just like you!
Sign up right now, and we’ll see you – on the other side!
Who are these people? for:
This course will help you learn how to load Python before you start R. This course introduces you to the basics of R. to These are the fundamentals that you should know before you begin to get involved. “Hands on”.
If you are interested in learning more about how it works, Machine Learning It is used for Data Science.
This includes business leaders, managers and app developers as well as consumers.
These are the people who are willing to take risks and be adventurous to Get ready to explore the exotic world of Data Science And Machine Learning.
Here’s what you’ll get in Introduction to Machine Learning for Data Science
IMPORTANT: This is it. “Introduction to Machine Learning for Data Science” It is totally Downloadable Available to We will immediately notify you (in the event of a broken or lost link), We appreciate your patience.
