Model tuning and deployment of neural networks for beginners
What you'll learn
- You will be able tune you own neural networks
- You will use Transfer learning
- You will learn a fast and easy way to deploy your models on your local host
- You will use an alternative python library to flask
- You will train your data science skills
- We will solve a Image multi classification task together
- Bonus (Deploy our model on google cloud app engine) (free of charge but requires a credit card registration)
Course content
- Preview00:47
- 00:02Download all resources here
- Preview07:40
- Preview09:30
- 12:263 Datapreparation and preprocessing for our network
- 10:304 Creating and training our baseline model
- 07:305 How to create a better model
- 11:466 How to improve our neural network performance - a more advanced network
- 18:417 Hyperparameter tuning for our neural network model
- 10:098 Tuned Model output and making predictions
- 10:029 Transferlearning - importing the libaries
- 08:3310 Transferlearning - data preprocessing steps
- 12:2311 Transferlearning - Training and making predictions
- 03:4012 Lets try out a second pretrained neural network model
- 10:4413 Introduction to creating websites with streamlit in python
- 09:1314 Introduction to creating websites with streamlit in python 2
- 19:3115 Creating our final model template and make predictions on uploaded images
- 00:13Resources for bonus lectures
- 00:43Important to know before diving into the Bonus videos
- 06:56Bonus Setup the Github environment and files
- 04:56Google Cloud App Engine Setup
- 01:39Final test deployment result
- 00:04NEW - A free resource for bonus videos tips and tricks
- 00:22You want to improve your data science skills?
- 00:2916 Final words
Requirements
- Basic knowlege of python
- Basic knowledge about neural networks
- This is a beginners class. We will code everything together step by step
- This course is hands on - instead of theory we implement the code and I explain what we do and why we do it
- Your personal interest in the topic and a hands on mentality
Description
About this course
Let's dive (again) into data science with python and learn how to solve a multi image classification challenge using tensorflow. We learn how to automatically tune our machine learning / neural network models. We also apply transfer learning. Finally we learn about a smart and easy way in python to create a website and deploy machine learning models (no HTML needed!)
This course is a complement to my other course
"Deploying machine learning models with flask for beginners"
This is a beginners class. You don't need to be an advanced data scientist but you should know about neural networks and python. We will learn and code step by step together and I will explain what we do along the way.
All the resources will be provided and you can download all the used tools completely for free.
Sounds interesting? I hope so! Let's dive in and do this together. Let's acquire new skills and create new opportunities for us.
Let's begin!
Who this course is for:
- beginners to intermediate students in neural networks and machine learning who already know the basics
- students who are eager to learn and dive into one of the hottest topics currently out there
- You want to learn how to deploy machine learning models
- You want to learn how to deploy neural networks
Instructor
![Dan We](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 4.4 Instructor Rating
- 9,959 Reviews
- 42,364 Students
- 51 Courses
Dan is a 31 year old entrepreneur ,data scientist and data analytics / visual analytics consultant. He holds a master degree and is certified in Power BI as well as a Qualified Associate in Tableau software. He is currently working in Business Intelligence field and helps major companies to get key insights from their data to deliver long term growth and outpace their competitors.
He is committed to support other people by offering them educational services to help them accomplishing their goals and becoming the best in their profession or explore a new career path.
"Helping others is the greatest joy"
"In order to do the impossible you need to see the invisible"
"If you don't like where you are then change. Life is too short!"
You can do it!