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Deep Learning and Machine Learning for Stocks Masterclass

Course Details
Trainer Name

Alexandra Kropova

Skill Area

Digital Technologies and Digital Transformation

Reviews

4.5 (24 Rating)

Course Requirements

Complete Beginners and Intermediate market participants.

Course Description

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.

Course Outcomes

1.You will completely understand how the Stock Market works.
2.You will understand what a Stock is, why you need a Broker
3.what are Exchanges.

Course Curriculum

1 How to Learn Online Effectively

2 About Mammoth Interactive

1 What is Supervised Learning

2 Types of Machine Learning Models

3 What is Machine Learning

1 Collections

2 While Loops Examples

3 Loops

4 If Statement Variants Examples

5 If Statement Examples

6 Conditionals

7 Ranges Examples

8 Dictionaries Examples

9 Tuples Examples

10 Multidimensional List Examples

11 Lists

12 For Loops Examples

13 Operators Examples

14 Operators

15 Type Conversion Examples

16 Variables

17 Intro To Python

18 Introduction

19 Summary and Outro

20 Static Members Example

21 Inheritance Examples

22 Objects Examples

23 Classes Example

24 Classes and Objects

25 Parameters And Return Values Examples

26 Functions Examples

27 Functions

1 Regression Applications in Finance

1 Project Preview

2 Visualize Model Results

3 Make a Prediction with Linear Regression

4 Preprocess Data for Machine Learning

5 What is Linear Regression

1 Find Best Polynomial Model

2 Make a Prediction with Higher Dimensionality Polynomial Regression.mp4

3 Make a Prediction with a 1D Polynomial

4 Preprocess Data for Polynomial Regression

5 Project Preview

1 Analyze Model Metrics

2 Evaluate Model Results

3 Make a Prediction with Logistic Regression

4 Preprocess Data for Logistic Regression

5 What is Logistic Regression

6 Project Preview

1 Train and Evaluate the Model

2 Build an Isotonic Regression Model

3 Load Data for Isotonic Regression

4 What is Isotonic Regression

5 Project Preview

1 Tree Applications in Finance

1 Project Preview

2 Build a Decision Tree

3 Preprocess Data for Decision Tree Classification

4 Make Decisions with Decision Trees

1 Train Model on Most Important Features

2 Visualize Feature Importance

3 Train a Random Forest Classifier

4 Preprocess Data for Random Forest Classification

5 What is the Random Forest Classifier Model

6 Project Preview

1 Project Preview

2 What is K Nearest Neighbours

3 Train a K Nearest Neighbors Classifier

4 Preprocess Data for K Nearest Neighbors

5 How k-NN Works

1 Visualize Clusters

2 Build K Means Clustering Models

3 Preprocess Data for Clustering

4 Load Data

5 What is K Means Clustering

6 What is Unsupervised Learning

7 Project Preview

1 Neural Network Applications in Finance

2 What is a Bernoulli Restricted Boltzmann Machine

3 What is a Neural Network

4 What is Deep Learning

1 Build a Neural Network

2 Load Data for Neural Network

3 Project Preview

1 Evaluate the Neural Network

2 Build a Neural Network

3 Load Data for Classifier

4 Project Preview

Trainer

Trainer Name

Alexandra Kropova

4.5 Rating
24 Reviews

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This course includes:

  • Duration: 11 Hours 17 Min

  • Skill Level: Beginner

  • Lectures: 88 lessons

  • Enrolled: 253 learners

  • Certificate of Completion

  • Lifetime access

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