English | MP4 | AVC 1280×720 | AAC 48KHz 2ch | 27 Hours | 15.6 GB
Want to learn ES6 development and TensorFlow stock market prediction modeling? Build your first web app in this course!
In Python & JS Masterclass: Build TensorFlow & ES6 Projects, you will learn the fundamentals of coding in JavaScript, including ES6. You will learn how to change what is displayed on a webpage using JavaScript.
No prior experience in JavaScript is required. We will explore ES6 in depth and cover many of its new features. You will learn the newest possibilities and fundamental building blocks of JavaScript.
- Get started with JavaScript basics
- Learn about ES6 and its new features
- Apply ES6 concepts in your projects
- Use build tools like Gulp and Webpack
- Compile ES6 into ES5 using Babel
Predict the Stock Market with Automated Tasks
You will learn how to code in Python 3, calculate linear regression with TensorFlow, and make a stock market prediction app. We interweave theory with practical examples so that you learn by doing.
Learn how to code in Python, a popular coding language used for websites like YouTube and Instagram.
Learn TensorFlow and how to build models of linear regression.
Build stock market prediction models for integration into apps!
Blend Theory with Hands On Coding Projects!
You will learn how to build an impressive model with a single variable. We don’t go into daily stock market prediction.
Build Powerful Web Apps with ES6
With ES6 (ECMAScript 6th Edition), you can code for the web. ECMAScript is another name for JavaScript. ES6 has standardized features that JavaScript engines implement. ES6 is well-supported across different web browsers.
Become a Data Scientist Today
You too can become a web developer by learning the popular programming language JavaScript. You’ll also learn hands-on Python coding, TensorFlow logistic regression, regression analysis, machine learning, and data science!
What Will I Learn?
- Build web apps using JavaScript ES6!
- Code in JavaScript and Python.
- Calculate linear regression in the TensorFlow framework.
- Make an app with Python that uses data to predict the stock market.
- Build impressive models with a single variable.
- Understand where to use machine learning and how to use data.
- Navigate the PyCharm integrated development environment.
- Download all source code and files from projects.
- And much more in this epic Mammoth Interactive course!
Table of Contents
Introduction to ES6
1 What is ES6
2 Functionality of ES6
3 Testing your Code
4 ES6 Common Pitfalls
5 ES6 Important Things to Know
6 Tips to get started with Javascript
7 Top 7 Things You will Learn about ES6
Basic Types
8 Numbers and Strings
9 Booleans
10 Booleans (Cont’d)
11 Objects
12 Objects (Cont’d)
13 Arrays
14 Arrays (Cont’d)
15 Source Basic Types
Variables
16 Intro to Variables Part 1
17 Intro to Variables Part 2
18 Intro to variables Part 3
19 Intro to variables Part 4
20 Scoping and Intro to Let
21 Let Statements (Cont’d)
22 Intro to Const
23 Summary
Operators
24 Intro to If Statements
25 Equal Sign Operators
26 Other Comparison Operators
27 Nested If Statements
28 Logical Operators
29 Not Operators
30 Else and Else If
Functions
31 Intro to Functions
32 Intro to Functions part 2
33 Intro to Functions Part 3
34 Hoisting
35 Function Expressions
36 Functions Changing Non-Primitive Properties
37 Nested Functions Part 1
38 Nested Functions Part 2
39 Nested Functions Part 3
More Functions
40 Function Expressions
41 Returns and Brackets
42 More Examples
43 More Examples (Cont’d)
44 Default Values
45 Rest Parameters
46 Arrow Functions
47 Arrow Functions (Cont’d)
Switch Statements
48 Switch Statements Part 1
49 Switch Statements Part 2
50 Switch Statements Part 3
51 Switch Statements Part 4
52 Switch Statements Part 5
Loops
53 Intro to Loops
54 For…In and For Each
55 For…of
56 For…of (Cont’d)
57 While Loops
58 While Loops (Cont’d)
59 Do While Loop
60 Do While Loop (Cont’d)
61 For Loop
62 For Loop (Cont’d)
63 Controlling Loops
64 Closing Over For Loop
DOM
65 Intro to DOM
66 Getting and Setting ID and CLass Part 2.
67 Getting and Setting ID and CLass Part 3
68 Getting and Setting ID and Class Part 4
69 Creating and Appending Elements
70 Creating and Appending Elements (Cont’d)
71 Removing Elements
72 Intro to DOM (cont’d)
73 getElementbyId Part 1
74 getElementbyId Part 2
75 getElementbyId Part 3
76 dom Query Selector
77 DOM Query Selector all
78 Traversing the DOM
79 Getting and Setting ID and Class Part 1
Events
80 Intro To Events
81 DOMContentLoaded
82 Load Event
83 Load Event (Cont’d)
84 Recommendations
85 Intro to Events (Cont’d)
86 Firing and Function Removing Events
87 Events Propagation
88 Common Design Pattern
89 Prevent Default
90 Prevent Default (Cont’d)
91 Key Events
92 Key Events (Cont’d)
Template Literals
93 Template Literals Part 1
94 Template Literals Part 2
95 Template Literals Part 3
96 Template Literals Part 4
97 Template Literals Part 5
Destructuring
98 Destructuring Arrays Part 1
99 Destructuring Arrays Part 2
100 Destructuring Arrays Part 3
101 Destructuring Objects Part 1
102 Destructuring Objects Part 2
103 Destructuring Objects Part 3
104 Destructuring Objects Part 4
105 Destructuring Nested Objects
106 Destructuring Nested Objects (cont’d)
Throw Exceptions and Try…Catch
107 Throw Exceptions
108 Throw Exceptions (Cont’d)
109 Try…Catch Part 1
110 Try…Catch Part 2
111 Try…Catch Part 3
112 Finally Statement
113 Final Thoughts
Object-Oriented Programming Language
114 OOP in JS intro Part 1
115 Inheriting from Objects Part 2
116 Inheriting from Objects Part 3
117 OOP in JS intro Part 2
118 OOP in JS Intro Part 3
119 OOP in JS Intro Part 4
120 OOP in JS Intro Part 5
121 Object Constructors Part 1
122 Object Constructors Part 2
123 Object Constructors Part 3
124 Inheriting from Objects Part 1
Classes, Inheritance and Grouping
125 Intro to Classes
126 Functions And Looping Practice (Cont’d)
127 Final Thoughts
128 Intro to Classes (Cont’d)
129 Inheritance Part 1
130 Inheritance Part 2
131 Inheritance Part 3
132 Static Methods
133 Pros and Cons of Inheritance
134 Grouping Without Inheritance
135 Functions and Looping Practice
Callbacks and Promises
136 Callbacks Part 1
137 Promises Part 3
138 Promises Part 4
139 Promises Part 5
140 Promises Part 6
141 Promises Part 7
142 Promises Part 8
143 Promises Part 9
144 Promises Part 10
145 Callbacks Part 2
146 Callbacks Part 3
147 Callbacks Part 4
148 Callbacks Part 5
149 Callbacks Part 6
150 Callbacks Part 7
151 Promises Part 1
152 Promises Part 2
Data and Attributes
153 Introduction
154 Fetching and Processing Data
155 Alternative Way to Append to HTML
156 Multiple Objects in Response
157 Multiple Objects in Response (Cont’d)
158 Loops and Data Attributes Part 1
159 Looping and Data Attribute Part 2
160 Loops and Data Attributes Part 3
161 Final Thoughts
Syntax and Property
162 Spread Syntax Part 1
163 Property Names (Cont’d)
164 Maps
165 Sets
166 Sets (Cont’d)
167 Final Thoughts
168 Spread Syntax Part 2
169 Spread Syntax Part 3
170 Spread Syntax Part 4
171 Spread Syntax Part 5
172 Rest Syntax and Method Definitions
173 Property Shorthand
174 Property Shorthand (Cont’d)
175 Property Names
Using Babel CLI and Gulp
176 Transpiling in Browser
177 Compile Using Gulp Part 4
178 Compile Using Gulp Part 5
179 Compiling Using Gulp Part 6
180 Using Babel CLI Part 1
181 Using Babel CLI Part 2
182 Using Babel CLI Part 3
183 Setting up Simple Server
184 Setting up Simple Server (Cont’d)
185 Compile Using Gulp Part 1
186 Compile Using Gulp Part 2
187 Compile Using Gulp Part 3
Linting, Bundling and Dev Server
188 Introduction
189 Dev Server (Cont’d)
190 Watch for Changes
191 Linting with eslint
192 Linting with eslint continued
193 Bundling Part 1
194 Bundling Part 2
195 Bundling Part 3
196 Bundling Part 4
197 Dev Server
ES6 Source Code
198 ES6 Source Code – Mammoth Interactive
Python Basics
199 What is Python Artificial Intelligence
200 Installing Python and Pycharm
201 How to Use Pycharm
202 Intro and Variables
203 Multivalue Variables
204 Control Flow
205 Functions
206 Classes and Wrap Up
207 Source Code
TensorFlow Basics
208 Installing TensorFlow
209 Intro and Setup
210 What is Tensorflow
211 Constant and Operation Nodes
212 Placeholder Nodes
213 Variable Nodes
214 How to Create Linear Regression Model
215 Building Linear Regression Model
216 Source Code
Stock Market Prediction
217 Introduction
218 Stock Market Prediction Model
219 Please rate this course
220 Bonus Lecture – Mammoth Interactive Deals
221 Project Overview
222 Understanding the Datasets
223 Importing and Formatting the Data we Want
224 Calculating Price Differences
225 Building the Computational Graph
226 Training the Model
227 Testing Model Accuracy
228 Summary and Outro
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