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Crypto Data Science And Ml With Python - AD-TEAM - 12-10-2024

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Crypto Data Science And Ml With Python
Published 8/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 3.91 GB | Duration: 11h 24m

Build 12 Models, Decentralized Federated Learning and More

What you'll learn
Regression Machine Learning with Blockchain API
Clustering Machine Learning on Cryptocurrencies
Build a K Nearest Neighbors Model
Build a Radius Neighbors Regression Model
Requirements
No experience necessary
Description
Buff your skills to keep your job and get a raise in ANY economic climate. This course BUNDLE keeps your skills sharp and your paycheque up!Data Science and Machine LearningBuild linear and polynomial regression machine learning models with Blockchain APICluster cryptocurrencies with machine learning techniquesClassify cryptocurrency data with machine learningBuild neural networks with Google's TensorFlow on cryptocurrency stock dataDifferential Privacy and Federated LearningBuild a differential privacy project to encrypt datasetsBuild a deep learning differential privacy queryEncrypt data sent to a machine learning model with federated learningThis masterclass is without a doubt the most comprehensive course available anywhere online. Even if you have zero experience, this course will take you from beginner to professional.Frequently Asked QuestionsHow do I obtain a certificate?Each certificate in this bundle is only awarded after you have completed every lecture of the course.Many of our students post their Mammoth Interactive certifications on LinkedIn. Not only that, but you will have projects to show employers on top of the certification.Is this an eBook or videos?The majority of this course bundle will be video tutorials (screencasts of practical coding projects step by step.) We will also have several PDFs and all source code.Can't I just learn via Google or YouTube?This bundle is much more streamlined and efficient than learning via Google or YouTube. We have curated a massive 5-course curriculum to take you from absolute beginner to starting a high-paying career.How will I practice to ensure I'm learning?With each section there will be a project, so if you can build the project along with us you are succeeding. There is also a challenge at the end of each section that you can take on to add more features to the project and advance the project in your own time.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. 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. Try a course today.

Overview

Section 1: Introduction

Lecture 1 Introduction

Section 2: 00b What is Blockchain

Lecture 2 00 How Blockchain Was Invented

Lecture 3 01 Blockchain Introduction

Lecture 4 02 What Is Bitcoin Mining

Section 3: 01 What is Machine Learning

Lecture 5 01 What Is Machine Learning

Lecture 6 02 What Is Supervised Learning

Section 4: 03 Regression Machine Learning with Blockchain API

Lecture 7 00A Project Preview

Lecture 8 00B What Is Linear Regression

Lecture 9 01 Collect Data From Blockchain Api

Lecture 10 02 Join CSV Files With Blockchain Data

Lecture 11 03 Process Data

Lecture 12 04 Visualize Data

Lecture 13 05 Create X And Y

Lecture 14 06 Build A Linear Regression Model

Lecture 15 07 Build A Polynomial Regression Model

Section 5: 04 Clustering Machine Learning on Cryptocurrencies

Lecture 16 00A Project Preview

Lecture 17 00B What Is Unsupervised Learning

Lecture 18 01 Collect Crypto Data With Cryptocompare API

Lecture 19 02 Clean Data

Lecture 20 03 Process Text Features

Lecture 21 04A What Is Principal Component Analysis

Lecture 22 04B Reduce Data Dimensionality With Principal Component Analysis

Lecture 23 05A What Is K Means Clustering

Lecture 24 05B Cluster Cryptocurrencies With K-Means Clustering

Lecture 25 06 Machine Learning With Optimal Number Of Clusters

Lecture 26 07 Visualize Clusters

Section 6: 05a Build a K Nearest Neighbors Model

Lecture 27 01 What Is K Nearest Neighbours

Lecture 28 02 Scrape Crypto Data With Yahoo Finance API

Lecture 29 03 Process Data

Lecture 30 04 Build A K-Nearest Neighbors Classifier

Lecture 31 05 Calculate Error For Different K Values

Section 7: 05b Build a Radius Neighbors Regression Model

Lecture 32 00 What Is Radius Neighbors Machine Learning

Lecture 33 01 Load Stock Data With Yahoo Finance API

Lecture 34 02 Build X And Y Training And Testing Data

Lecture 35 03 Build A Radius Neighbors Regression Model

Section 8: 06a Build a CatBoost Model

Lecture 36 00 What Is Catboost Machine Learning

Lecture 37 00B What Is Gradient Boosting

Lecture 38 01 Load Data

Lecture 39 02 Process Data

Lecture 40 03 Build A Catboost Classifier Model

Section 9: 06b Build an XGBoost Regression Model

Lecture 41 01 Load Stock Data With Yahoo Finance API

Lecture 42 02 Build An XGboost Regression Model

Section 10: 07a Neural Network Fundamentals

Lecture 43 01 What Is Deep Learning

Lecture 44 02 What Is A Neural Network

Section 11: 07b Build a Neural Network Classifier

Lecture 45 01 Load Stock Data With Yahoo Finance API

Lecture 46 02 Build X And Y Training And Testing Data

Lecture 47 03 Build A Neural Network Classifier

Lecture 48 04 Calculate Neural Network Accuracy From Confusion Matrix

Section 12: 07c Build a Recurrent Neural Network with TensorFlow

Lecture 49 00A Project Preview

Lecture 50 00B What Is A Recurrent Neural Network

Lecture 51 01 Load Stock Data With Yahoo Finance API

Lecture 52 02 Visualize Data

Lecture 53 03 Build A Training Dataset

Lecture 54 04 Build Features And Labels

Lecture 55 05 Build A Tensorflow LSTM Neural Network

Lecture 56 06 Load Test Data With An API

Lecture 57 07 Build Features And Labels For Testing The Neural Network

Lecture 58 08 Visualize Model's Predictions

Section 13: 08 Build a Bagging Classifier Model

Lecture 59 00A Bagging And Decision Trees Introduction

Lecture 60 00B How Bagging Works

Lecture 61 01 Load Stock Data With Yahoo Finance API

Lecture 62 02 Build X And Y Training And Testing Data

Lecture 63 03 Train And Test A Bagging Classifier

Section 14: 09 Build a Light Gradient Boosted Regression Ensemble

Lecture 64 00A Gradient Boosting Introduction

Lecture 65 00B What Is A Light Gradient Boosted Regression Ensemble

Lecture 66 01 Load Stock Data With Yahoo Finance API

Lecture 67 02 Build A Light GBM

Lecture 68 03 Find Best Number Of Trees

Lecture 69 04 Find Best Tree Depth

Section 15: 10 Build a Nested Cross Validation Model

Lecture 70 00 What Is Nested Cross Validation

Lecture 71 01 Load Stock Data With Yahoo Finance Api

Lecture 72 02 Build More Features

Lecture 73 03 Define X And Y

Lecture 74 04 Implement Cross Validated Grid Search

Section 16: 11 Differential Privacy Project

Lecture 75 00 What Is Differential Privacy

Lecture 76 01 Differential Privacy Project Introduction

Lecture 77 02 Build An Initial Database

Lecture 78 03 Build A Parallel Database

Lecture 79 04 Build Multiple Parallel Databases

Lecture 80 05 Determine If Query Leaks Private Data

Lecture 81 06 Calculate Sensitivity Of Mean Query

Lecture 82 07 Build Local Differential Privacy

Section 17: 12 Deep Learning Differential Privacy Project

Lecture 83 00 Deep Learning Differential Privacy Introduction

Lecture 84 01 Build Database

Lecture 85 02 Build A Differential Privacy Query

Lecture 86 03 Perform Pate Analysis

Section 18: 13 Build a Federated Learning Model

Lecture 87 00 What Is Federated Learning

Lecture 88 01 Generate A Dataset

Lecture 89 02 Build A Regular Model

Lecture 90 03 Visualize Model Results

Lecture 91 04 Build A Client-Side Model

Lecture 92 05 Build An Aggregator Model

Lecture 93 06 Generate Clients Dataset

Lecture 94 07 Execute The Federated Learning Model

Lecture 95 08 Evaluate The Model

Anyone interested in machine learning with a blockchain emphasis

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