Deep Learning Machine Learning Practical

Build 8 Practical Projects and Go from Zero to Hero in Deep/Machine Learning, Artificial Neural Networks

Last updated 2022-01-10 | 4.6

- Deep Learning Practical Applications
- Machine Learning Practical Applications
- How to use ARTIFICIAL NEURAL NETWORKS to predict car sales

What you'll learn

Deep Learning Practical Applications

Machine Learning Practical Applications

How to use ARTIFICIAL NEURAL NETWORKS to predict car sales

How to use DEEP NEURAL NETWORKS for image classification

How to use LE-NET DEEP NETWORK to classify Traffic Signs

How to apply TRANSFER LEARNING for CNN image classification

How to use PROPHET TIME SERIES to predict crime

How to use PROPHET TIME SERIES to predict market conditions

How to develop NATURAL LANGUAGE PROCESSING MODEL to analyze Reviews

How to apply NATURAL LANGUAGE PROCESSING to develop spam filder

How to use USER-BASED COLLABORATIVE FILTERING to develop recommender system

* Requirements

* Deep Learning and Machine Learning basics
* PC with Internet connetion

Description

Deep Learning Practical Applications
Machine Learning Practical Applications
How to use ARTIFICIAL NEURAL NETWORKS to predict car sales
How to use DEEP NEURAL NETWORKS for image classification
How to use LE-NET DEEP NETWORK to classify Traffic Signs
How to apply TRANSFER LEARNING for CNN image classification
How to use PROPHET TIME SERIES to predict crime
How to use PROPHET TIME SERIES to predict market conditions
How to develop NATURAL LANGUAGE PROCESSING MODEL to analyze Reviews
How to apply NATURAL LANGUAGE PROCESSING to develop spam filder
How to use USER-BASED COLLABORATIVE FILTERING to develop recommender system

Course content

11 sections • 90 lectures

INTRODUCTION TO THE COURSE [QUICK WIN IN FIRST 10-12 MINS] 9 lectures

Welcome Message Preview 02:43

Updates on Udemy Reviews Preview 01:04

Course overview Preview 08:35

BONUS: Learning Path Preview 00:33

ML vs. DL vs. AI Preview 16:15

Download Course Materials Preview 00:04

BONUS: ML vs DL vs AI Preview 00:26

BONUS: 5 Benefits of Jupyter Notebook Preview 00:59

ANACONDA AND JUPYTER INSTALLATION 4 lectures

Download and Set up Anaconda Preview 04:12

What is Jupyter Notebook Preview 03:34

Install Tensorflow Preview 00:05

How to run a Jupyter Notebook Preview 10:37

PROJECT #1: ARTIFICIAL NEURAL NETWORKS - CAR SALES PREDICTION 12 lectures

Theory Part 1 Preview 13:01

Theory Part 2 Preview 06:58

Theory Part 3 Preview 10:14

Theory Part 4 Preview 06:37

Theory Part 5 Preview 05:26

Project Overview Preview 07:14

Data Visualization Cleaning Preview 21:12

Model Training 1 Preview 18:25

Model Training 2 Preview 09:49

Model Evaluation Preview 12:30

PROJECT #2: DEEP NEURAL NETWORKS - CIFAR-10 CLASSIFICATION 14 lectures

Theory Part 1 Preview 05:56

Theory Part 2 Preview 17:08

Theory Part 3 Preview 12:59

Theory Part 4 Preview 16:06

Problem Statement Preview 09:13

Data Vizualization Preview 15:38

Data Preparation Preview 09:58

Model Training Part 1 Preview 16:56

Model Training Part 2 Preview 12:14

Model Evaluation Preview 14:24

Save the Model Preview 04:40

Image Augmentation Part 1 Preview 16:19

Image augmentation Part 2 Preview 13:06

PROJECT #3: PROPHET TIME SERIES - CHICAGO CRIME RATE 6 lectures

Project Overview Preview 07:16

Import Dataset Preview 07:27

Data Vizualization Preview 29:18

Prepare the Data Preview 04:55

Make Predictions Preview 08:46

PROJECT #4: PROPHET TIME SERIES - AVOCADO MARKET 6 lectures

Load Avocado Data Preview 09:02

Explore Dataset Preview 14:07

Make Predictions Part 1 Preview 09:52

Make Predictions Part 2 (Region Specific) Preview 05:28

Make Prediction Part 2.1 Preview 06:14

PROJECT #5: LE-NET DEEP NETWORK - TRAFFIC SIGN CLASSIFICATION 7 lectures

Project Overview Preview 09:11

Data Exploration Preview 07:46

Data Normalization Preview 14:03

Model Training Preview 26:38

Model Evaluation Preview 21:15

PROJECT #6: NATURAL LANGUAGE PROCESSING - E-MAIL SPAM FILTER 9 lectures

Naive Bayes Theory Part 1 Preview 16:06

Naive Bayes Theory Part 2 Preview 14:55

Spam Project Overview Preview 09:25

Visualize Dataset Preview 09:54

Count Vectorizer Preview 14:12

Model Training Part 1 Preview 09:01

Model Training Part 2 Preview 05:08

PROJECT #7: NATURAL LANGUAGE PROCESSING - YELP REVIEWS 15 lectures

Project Overview Preview 06:11

Visualize Dataset Part 1 Preview 18:01

Visualize Dataset Part 2 Preview 10:52

Apply NLP to Data Preview 13:40

Apply Count Vectorizer to Data Preview 04:53

Model Training Part 1 Preview 07:55

Model Training Part 2 Preview 05:31

Model Evaluation Part 1 Preview 06:17

Model Evaluation Part 2 Preview 12:50

PROJECT #8: USER-BASED COLLABORATIVE FILTERING - MOVIE RECOMMENDER SYSTEM 7 lectures

Project Overview Preview 03:39

Import Movie Dataset Preview 15:15

Visualize Dataset Preview 20:36

Collaborative Filter One Movie Preview 21:55

Full Movie Recomendation Preview 12:45

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