Artificial Intelligence with Crypto Stocks

Focused View

John Bura,Mammoth Interactive

11:39:40

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1 - 00a Course Overview

1 - 00 Course Overview Blockchain Machine Learning.mp4

09:14

2 - 00b What is Blockchain

2 - 00 How Blockchain Was Invented.mp4

07:26

3 - 01 Blockchain Introduction.mp4

08:32

4 - 02 What Is Bitcoin Mining.mp4

05:11

3 - 00c Mammoth Interactive Courses Introduction

5 - 00 About Mammoth Interactive.mp4

01:12

6 - 01 How To Learn Online Effectively.mp4

13:46

4 - 01 What is Machine Learning

7 - 01 What Is Machine Learning.mp4

05:26

8 - 02 What Is Supervised Learning.mp4

10:40

5 - 03 Regression Machine Learning with Blockchain API

9 - 00A Project Preview.mp4

02:12

10 - 00B What Is Linear Regression.mp4

05:03

11 - 01 Collect Data From Blockchain API.mp4

12:57

12 - 02 Join CSV Files With Blockchain Data.mp4

09:01

13 - 03 Process Data.mp4

04:06

14 - 04 Visualize Data.mp4

11:19

15 - 05 Create X And Y.mp4

06:15

16 - 06 Build A Linear Regression Model.mp4

04:59

17 - 07 Build A Polynomial Regression Model.mp4

05:53

18 - Source Files.html

18 - Source-Files.zip

6 - 04 Clustering Machine Learning on Cryptocurrencies

19 - 00A Project Preview.mp4

03:02

20 - 00B What Is Unsupervised Learning.mp4

08:17

21 - 01 Collect Crypto Data With Cryptocompare API.mp4

09:35

22 - 02 Clean Data.mp4

08:10

23 - 03 Process Text Features.mp4

07:26

24 - 04A What Is Principal Component Analysis.mp4

07:27

25 - 04B Reduce Data Dimensionality With Principal Component Analysis.mp4

04:41

26 - 05A What Is K Means Clustering.mp4

11:58

27 - 05B Cluster Cryptocurrencies With KMeans Clustering.mp4

07:41

28 - 06 Machine Learning With Optimal Number Of Clusters.mp4

04:48

29 - 07 Visualize Clusters.mp4

05:25

30 - Source Files.html

30 - Source-Files.zip

7 - 05a Build a K Nearest Neighbors Model

31 - 01 What Is K Nearest Neighbors.mp4

08:07

32 - 02 Scrape Crypto Data With Yahoo Finance API.mp4

07:58

33 - 03 Process Data.mp4

15:33

34 - 04 Build A KNearest Neighbors Classifier.mp4

10:08

35 - 05 Calculate Error For Different K Values.mp4

06:38

36 - Source Files.html

36 - Source-Files.zip

8 - 05b Build a Radius Neighbors Regression Model

37 - 00 What Is Radius Neighbors Machine Learning.mp4

05:03

38 - 01 Load Stock Data With Yahoo Finance API.mp4

06:59

39 - 02 Build X And Y Training And Testing Data.mp4

05:11

40 - 03 Build A Radius Neighbors Regression Model.mp4

07:30

41 - Source Files.html

41 - Source-Files.zip

9 - 06a Build a CatBoost Model

42 - 00 What Is Catboost Machine Learning.mp4

02:26

43 - 00B What Is Gradient Boosting.mp4

08:38

44 - 01 Load Data.mp4

04:51

45 - 02 Process Data.mp4

10:53

46 - 03 Build A Catboost Classifier Model.mp4

07:31

47 - Source Files.html

47 - Source-Files.zip

10 - 06b Build an XGBoost Regression Model

48 - 01 Load Stock Data With Yahoo Finance API.mp4

04:35

49 - 02 Build An XGboost Regression Model.mp4

07:27

50 - Source Files.html

50 - Source-Files.zip

11 - 07a Neural Network Fundamentals

51 - 01 What Is Deep Learning.mp4

07:42

52 - 02 What Is A Neural Network.mp4

08:47

12 - 07b Build a Neural Network Classifier

53 - 01 Load Stock Data With Yahoo Finance API.mp4

07:20

54 - 02 Build X And Y Training And Testing Data.mp4

06:13

55 - 03 Build A Neural Network Classifier.mp4

06:30

56 - 04 Calculate Neural Network Accuracy From Confusion Matrix.mp4

09:30

57 - Source Files.html

57 - Source-Files.zip

13 - 07c Build a Recurrent Neural Network with TensorFlow

58 - 00A Project Preview.mp4

02:12

59 - 00B What Is A Recurrent Neural Network.mp4

06:38

60 - 01 Load Stock Data With Yahoo Finance API.mp4

07:20

61 - 02 Visualize Data.mp4

08:27

62 - 03 Build A Training Dataset.mp4

08:04

63 - 04 Build Features And Labels.mp4

10:37

64 - 05 Build A Tensorflow Lstm Neural Network.mp4

12:05

65 - 06 Load Test Data With An API.mp4

07:32

66 - 07 Build Features And Labels For Testing The Neural Network.mp4

10:42

67 - 08 Visualize Models Predictions.mp4

08:42

68 - Source Files.html

68 - Source-Files.zip

14 - 08 Build a Bagging Classifier Model

69 - 00A Bagging And Decision Trees Introduction.mp4

05:25

70 - 00B How Bagging Works.mp4

07:11

71 - 01 Load Stock Data With Yahoo Finance API.mp4

08:34

72 - 02 Build X And Y Training And Testing Data.mp4

06:00

73 - 03 Train And Test A Bagging Classifier.mp4

07:34

74 - Source Files.html

74 - Source-Files.zip

15 - 09 Build a Light Gradient Boosted Regression Ensemble

75 - 00A Gradient Boosting Introduction.mp4

08:40

76 - 00B What Is A Light Gradient Boosted Regression Ensemble.mp4

05:08

77 - 01 Load Stock Data With Yahoo Finance API.mp4

05:08

78 - 02 Build A Light GBM.mp4

07:59

79 - 03 Find Best Number Of Trees.mp4

08:46

80 - 04 Find Best Tree Depth.mp4

05:23

81 - Source Files.html

81 - Source-Files.zip

16 - 10 Build a Nested Cross Validation Model

82 - 00 What Is Nested Cross Validation.mp4

14:29

83 - 01 Load Stock Data With Yahoo Finance Api.mp4

03:01

84 - 02 Build More Features.mp4

06:32

85 - 03 Define X And Y.mp4

05:55

86 - 04 Implement Cross Validated Grid Search.mp4

06:02

87 - Source Files.html

87 - Source-Files.zip

17 - 11 Differential Privacy Project

88 - 00 What Is Differential Privacy.mp4

07:18

89 - 01 Differential Privacy Project Introduction.mp4

13:16

90 - 02 Build An Initial Database.mp4

03:05

91 - 03 Build A Parallel Database.mp4

04:04

92 - 04 Build Multiple Parallel Databases.mp4

03:09

93 - 05 Determine If Query Leaks Private Data.mp4

05:12

94 - 06 Calculate Sensitivity Of Mean Query.mp4

06:29

95 - 07 Build Local Differential Privacy.mp4

09:09

96 - Source Files.html

96 - Source-Files.zip

18 - 12 Deep Learning Differential Privacy Project

97 - 00 Deep Learning Differential Privacy Introduction.mp4

13:22

98 - 01 Build Database.mp4

03:45

99 - 02 Build A Differential Privacy Query.mp4

04:10

100 - 03 Perform Pate Analysis.mp4

06:10

101 - Source Files.html

101 - Source-Files.zip

19 - 13 Build a Federated Learning Model

102 - 00 What Is Federated Learning.mp4

06:28

103 - 01 Generate A Dataset.mp4

10:03

104 - 02 Build A Regular Model.mp4

07:43

105 - 03 Visualize Model Results.mp4

07:01

106 - 04 Build A ClientSide Model.mp4

02:51

107 - 05 Build An Aggregator Model.mp4

02:07

108 - 06 Generate Clients Dataset.mp4

09:26

109 - 07 Execute The Federated Learning Model.mp4

09:58

110 - 08 Evaluate The Model.mp4

03:36

111 - Source Files.html

111 - Source-Files.zip

Description

Build 20 ML projects!

What You'll Learn?

Build machine learning models
Code in Python
Scrape blockchain data
Build federated learning models

Who is this for?

Anyone interested in machine learning on cryptocurrency

What You Need to Know?

No experience required

More details

Description
Artificial Intelligence with Crypto Stocks, get wild and crazy with all our cryptocurrency and blockchain lessons!
Some of our contents for this course include:
Build regression models with Blockchain data
Build clustering models on Cryptocurrency data
Build a K Nearest neighbors model on crypto data from Yahoo Finance
Build a radius neighbors regression model on stock data
Build a gradient boosting model
Build a neural network to classify stock data
Build a differential privacy project with a database
Build a federated model
And Much more
We will start you from the basics of what a blockchain is and then periodically expand your knowledge on it's many different applications.
Alexandra Kropova is a software developer with extensive experience in full-stack web development, app development and game development. She has helped produce courses for Mammoth Interactive since 2016, including the Coding Interview series in Java, JavaScript, C++, C#, Python and Swift.
When does the course start and finish?
The course starts now and never ends! It is a completely self-paced online course - you decide when you start and when you finish.
How long do I have access to the course?
How does lifetime access sound?
After enrolling, you have unlimited access to this course for as long as you like - across any and all devices you own.
Don't miss on this opportunity and get started today!
Who this course is for:
Anyone interested in machine learning on cryptocurrency

User Reviews

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Focused display

John Bura is has been a successful Udemy instructor since 2011. John Bura has been programming games since 1997 and teaching since 2002. John is the owner of the game development studio Mammoth Interactive. This company produces XBOX 360, iPhone, iPad, android, HTML 5, ad-games and more. Mammoth Interactive recently sold a game to Nickelodeon! John has been contracted by many different companies to provide game design, audio, programming, level design and project management. To this day John has 40 commercial games that he has contributed to. Several of the games he has produced have risen to the top 10 in the Apple's app store. In his spare time John likes to play ultimate Frisbee, cycle and work out.

Mammoth Interactive

Instructor's Courses

Mammoth Interactive is a leading online course provider in everything from learning to code to becoming a YouTube star. Mammoth Interactive courses have been featured on Harvard’s edX, Business Insider and more.Over 11 years, Mammoth Interactive has built a global student community with 1.1 million courses sold. Mammoth Interactive has released over 250 courses and 2,500 hours of video content.Founder and CEO John Bura has been programming since 1997 and teaching since 2002. John has created top-selling applications for iOS, Xbox and more. John also runs SaaS company Devonian Apps, building efficiency-minded software for technology workers like you."I absolutely love this course. This is such a comprehensive course that was well worth the money I spent and a lot more. Will definitely be looking at more Mammoth Interactive courses when I finish this." – Student Matt W."Very good at explaining the basics then building to more complex features." – Student Kevin L.Try a course today.

Udemy

View courses Udemy

Students take courses primarily to improve job-related skills.Some courses generate credit toward technical certification. Udemy has made a special effort to attract corporate trainers seeking to create coursework for employees of their company.