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Machine Learning for Apps.
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A comprehensive list of all sections & lectures for this course can be found below.
What is Machine Learning? - 07:47 [Play]
Basics of Machine Learning - 06:34
Installing Anaconda / Python Environment - 07:26
Downloading / Setting Up Atom and Plugins - 09:02
Variables in Python - 08:24 [Play]
Functions, Conditionals, and Loops in Python - 09:50
Arrays and Tuples in Python - 13:52
Importing Modules in Python - 05:22
What is scikit-learn? Why use it? - 03:52 [Play]
Installing scikit-learn and scipy with Anaconda - 03:28
Intro to the Iris Dataset - 03:28
Datasets: Features and Labels Explained - 07:39
Loading the Iris Dataset / Examining and Preparing Data - 09:27
Creating / Training a KNeighborsClassifier - 09:43
Testing Prediction Accuracy with Test Data - 12:08
Building Our Own KNeighborsClassifier - 18:00
What is Keras? Why use it? - 08:02 [Play]
What is a Convolutional Neural Network (CNN)? - 26:30
Installing Keras with Anaconda - 04:38
Preparing Dataset for a CNN - 17:38
Building / Visualizing a CNN using Sequential: Part 1 - 14:07
Building / Visualizing a CNN using Sequential: Part 2 - 19:41
Training CNN / Evaluating Accuracy / Saving to Disk - 17:54
Switching Python Environments / Converting to Core ML Model - 13:39
Intro to App â€“ Handwriting - 02:56 [Play]
Building Interface / Wiring Up - 11:43
Drawing On Screen - 21:01
Importing Core ML Model / Reading Metadata - 05:17
Utilizing Core ML / Vision to Make Prediction - 17:31
Handling / Displaying Prediction Results - 15:14
Intro to App â€“ Core ML Photo Analysis - 04:26 [Play]
What is Machine Learning? - 07:47
What is Core ML? - 05:04
Creating Xcode Project - 02:43
Building ImageVC in Interface Builder / Wiring Up - 07:41
Creating ImageCell - 08:13
Creating FoodItems Helper File - 07:02
Creating Custom 3x3 Grid UICollectionViewFlowLayout - 09:12
Choosing, Downloading, Importing Core ML Model - 05:18
Passing Images Through Core ML Model - 12:19
Handling Core ML Prediction Results - 09:42
Challenge â€“ Core ML Photo Analysis - 01:16
Brought to you by Devslopes LLC
Welcome to the most comprehensive course on Core ML, one of Apples hot new features for iOS 11. The goal with Machine Learning is to mimic the human mind. It can be used to identify things like objects or images, make predictions and even analyze and identify speech.
Dive in and learn the core concepts of machine learning and start building apps that can think! In this course you going to learn everything you need to know to start building more intelligent apps and your own ML Models.
Why Take this Course?
Core ML is the first step if you want to start building apps with AI. Machine Learning opens an entirely new world to opportunities that will take your apps to the next level.
All course reviews are written by students who have completed the course or are currently enrolled.
I hate using Atom editor, which this course heavily relies on. It keeps freezing on my computer. Other then that it has good information.
Extremely brilliant. Thank you for offering a great deal on this course!
Difficult to understand at first. If you are new to this stuff you may need to google a whole bunch of terms while taking the course.
Good job Caleb! Upload some more courses like this, I will take them!
Very useful information. I like the teacher as well, very easy to understand.
The intro hooked me in right away. Glad I registered. Seems like a good deal!
Good so far
Clear and easy to understand.
Does not seem like a beginner course to me! Way over my head, but mayeb I will watch it a few times :)
I am learning quite a bit. I do wish there was a little more real-world experience. It is a short course and a great introduction. ML requires in-depth knowledge of python. I would recommend taking a good python course to supplement the material taught here.
Nice and easy
New here, nice to meet you all. Does anyone here can help me to understand how download the zip files.
Caleb is a good teacher. I will take more of his classes if you offer them.
Easy to learn, I like this course.
I found some of the topics a bit basic. Too much theory. Best way to learn machine learning is coding while using sample data sets.
Just started, but loving it so far!
Helpful course on ML.
Certainly a 5 star course. Could not have asked for more.
Awesome course, please update me if you do another one.
I liked the course. I wish they uploaded more exercises and practice algorithms. An ML course is only as good as the data sets provided to the students. More data sets make learning more effective.
ML is awesome. It will be a game changer and those who took the time to learn it, will be ahead of the game for sure.
I found the course a bit geared towards MAC users, but it\'s not a big deal. It was definitely well structured with great coding excercises. I did learn a lot.
Well structured, and perfectly paced.
Finally, a great introduction into Machine Learning.
Good work, I would like to learn more.
Soon we will have self-driving cars, automated delivery, and machines able to learn. I\'m not sure where us humans fit into this new world :D
Up to date
Great videos. Look forward to more.
Not done the course, but good content so far.
This course is pretty short. I think they tried to fit too much information into a small amount of time. Good intro, but there is much more to know.
Easy to grasp
Complex information explained seamlessly. There is still much to learn about Machine Learning, but this course provides a great introduction in a short time.
Fantastic course. I watched another series on Machine learning, but this course was much more in-depth.
Good for the basics. I can?t get the downloads to work for the source files. Had the same issue in the other course.
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