Crypto Data Science and ML with Python

Crypto Data Science and ML with Python, available at $54.99, has an average rating of 4.6, with 95 lectures, based on 17 reviews, and has 243 subscribers.

You will learn about Regression Machine Learning with Blockchain API Clustering Machine Learning on Cryptocurrencies Build a K Nearest Neighbors Model Build a Radius Neighbors Regression Model This course is ideal for individuals who are Anyone interested in machine learning with a blockchain emphasis It is particularly useful for Anyone interested in machine learning with a blockchain emphasis.

Enroll now: Crypto Data Science and ML with Python

Summary

Title: Crypto Data Science and ML with Python

Price: $54.99

Average Rating: 4.6

Number of Lectures: 95

Number of Published Lectures: 95

Number of Curriculum Items: 95

Number of Published Curriculum Objects: 95

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

Regression Machine Learning with Blockchain API

Clustering Machine Learning on Cryptocurrencies

Build a K Nearest Neighbors Model

Build a Radius Neighbors Regression Model

Who Should Attend

Anyone interested in machine learning with a blockchain emphasis

Target Audiences

Anyone interested in machine learning with a blockchain emphasis

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 Learning

Build linear and polynomial regression machine learning models with Blockchain API

Cluster cryptocurrencies with machine learning techniques

Classify cryptocurrency data with machine learning

Build neural networks with Google’s TensorFlow on cryptocurrency stock data

Differential Privacy and Federated Learning

Build a differential privacy project to encrypt datasets

Build a deep learning differential privacy query

Encrypt data sent to a machine learning model with federated learning

This 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 Questions

How 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.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Chapter 2: 00b What is Blockchain

Lecture 1: 00 How Blockchain Was Invented

Lecture 2: 01 Blockchain Introduction

Lecture 3: 02 What Is Bitcoin Mining

Chapter 3: 01 What is Machine Learning

Lecture 1: 01 What Is Machine Learning

Lecture 2: 02 What Is Supervised Learning

Chapter 4: 03 Regression Machine Learning with Blockchain API

Lecture 1: 00A Project Preview

Lecture 2: 00B What Is Linear Regression

Lecture 3: 01 Collect Data From Blockchain Api

Lecture 4: 02 Join CSV Files With Blockchain Data

Lecture 5: 03 Process Data

Lecture 6: 04 Visualize Data

Lecture 7: 05 Create X And Y

Lecture 8: 06 Build A Linear Regression Model

Lecture 9: 07 Build A Polynomial Regression Model

Chapter 5: 04 Clustering Machine Learning on Cryptocurrencies

Lecture 1: 00A Project Preview

Lecture 2: 00B What Is Unsupervised Learning

Lecture 3: 01 Collect Crypto Data With Cryptocompare API

Lecture 4: 02 Clean Data

Lecture 5: 03 Process Text Features

Lecture 6: 04A What Is Principal Component Analysis

Lecture 7: 04B Reduce Data Dimensionality With Principal Component Analysis

Lecture 8: 05A What Is K Means Clustering

Lecture 9: 05B Cluster Cryptocurrencies With K-Means Clustering

Lecture 10: 06 Machine Learning With Optimal Number Of Clusters

Lecture 11: 07 Visualize Clusters

Chapter 6: 05a Build a K Nearest Neighbors Model

Lecture 1: 01 What Is K Nearest Neighbours

Lecture 2: 02 Scrape Crypto Data With Yahoo Finance API

Lecture 3: 03 Process Data

Lecture 4: 04 Build A K-Nearest Neighbors Classifier

Lecture 5: 05 Calculate Error For Different K Values

Chapter 7: 05b Build a Radius Neighbors Regression Model

Lecture 1: 00 What Is Radius Neighbors Machine Learning

Lecture 2: 01 Load Stock Data With Yahoo Finance API

Lecture 3: 02 Build X And Y Training And Testing Data

Lecture 4: 03 Build A Radius Neighbors Regression Model

Chapter 8: 06a Build a CatBoost Model

Lecture 1: 00 What Is Catboost Machine Learning

Lecture 2: 00B What Is Gradient Boosting

Lecture 3: 01 Load Data

Lecture 4: 02 Process Data

Lecture 5: 03 Build A Catboost Classifier Model

Chapter 9: 06b Build an XGBoost Regression Model

Lecture 1: 01 Load Stock Data With Yahoo Finance API

Lecture 2: 02 Build An XGboost Regression Model

Chapter 10: 07a Neural Network Fundamentals

Lecture 1: 01 What Is Deep Learning

Lecture 2: 02 What Is A Neural Network

Chapter 11: 07b Build a Neural Network Classifier

Lecture 1: 01 Load Stock Data With Yahoo Finance API

Lecture 2: 02 Build X And Y Training And Testing Data

Lecture 3: 03 Build A Neural Network Classifier

Lecture 4: 04 Calculate Neural Network Accuracy From Confusion Matrix

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

Lecture 1: 00A Project Preview

Lecture 2: 00B What Is A Recurrent Neural Network

Lecture 3: 01 Load Stock Data With Yahoo Finance API

Lecture 4: 02 Visualize Data

Lecture 5: 03 Build A Training Dataset

Lecture 6: 04 Build Features And Labels

Lecture 7: 05 Build A Tensorflow LSTM Neural Network

Lecture 8: 06 Load Test Data With An API

Lecture 9: 07 Build Features And Labels For Testing The Neural Network

Lecture 10: 08 Visualize Models Predictions

Chapter 13: 08 Build a Bagging Classifier Model

Lecture 1: 00A Bagging And Decision Trees Introduction

Lecture 2: 00B How Bagging Works

Lecture 3: 01 Load Stock Data With Yahoo Finance API

Lecture 4: 02 Build X And Y Training And Testing Data

Lecture 5: 03 Train And Test A Bagging Classifier

Chapter 14: 09 Build a Light Gradient Boosted Regression Ensemble

Lecture 1: 00A Gradient Boosting Introduction

Lecture 2: 00B What Is A Light Gradient Boosted Regression Ensemble

Lecture 3: 01 Load Stock Data With Yahoo Finance API

Lecture 4: 02 Build A Light GBM

Lecture 5: 03 Find Best Number Of Trees

Lecture 6: 04 Find Best Tree Depth

Chapter 15: 10 Build a Nested Cross Validation Model

Lecture 1: 00 What Is Nested Cross Validation

Lecture 2: 01 Load Stock Data With Yahoo Finance Api

Lecture 3: 02 Build More Features

Lecture 4: 03 Define X And Y

Lecture 5: 04 Implement Cross Validated Grid Search

Chapter 16: 11 Differential Privacy Project

Lecture 1: 00 What Is Differential Privacy

Lecture 2: 01 Differential Privacy Project Introduction

Lecture 3: 02 Build An Initial Database

Lecture 4: 03 Build A Parallel Database

Lecture 5: 04 Build Multiple Parallel Databases

Lecture 6: 05 Determine If Query Leaks Private Data

Lecture 7: 06 Calculate Sensitivity Of Mean Query

Lecture 8: 07 Build Local Differential Privacy

Chapter 17: 12 Deep Learning Differential Privacy Project

Lecture 1: 00 Deep Learning Differential Privacy Introduction

Instructors

Mammoth Interactive
Top-Rated Instructor, 3.3 Million+ Students

John Bura
Best Selling Instructor Web/App/Game Developer 1Mil Students

Rating Distribution

1 stars: 0 votes

2 stars: 1 votes

3 stars: 0 votes

4 stars: 5 votes

5 stars: 11 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!