Mô tả

In This Course, Solve Business Problems Using Data Science Practically. Learn To Build & Deploy Machine Learning, Data Science, Artificial Intelligence, Auto Ml, Deep Learning, Natural Language Processing (Nlp) Web Applications Projects With Python (Flask, Django, Heroku, AWS, Azure, GCP, IBM Watson, Streamlit Cloud).


According to Glassdoor, the average salary for a Data Scientist is $117,345/yr. This is above the national average of $44,564. Therefore, a Data Scientist makes 163% more than the national average salary.

This makes Data Science a highly lucrative career choice. It is mainly due to the dearth of Data Scientists resulting in a huge income bubble.

Since Data Science requires a person to be proficient and knowledgeable in several fields like Statistics, Mathematics, and Computer Science, the learning curve is quite steep. Therefore, the value of a Data Scientist is very high in the market.

A Data Scientist enjoys a position of prestige in the company. The company relies on its expertise to make data-driven decisions and enable them to navigate in the right direction.

Furthermore, the role of a Data Scientist depends on the specialization of his employer company. For example – A commercial industry will require a data scientist to analyze their sales.

A healthcare company will require data scientists to help them analyze genomic sequences. The salary of a Data Scientist depends on his role and type of work he has to perform. It also depends on the size of the company which is based on the amount of data they utilize.

Still, the pay scale of Data scientists is way above other IT and management sectors. However, the salary observed by Data Scientists is proportional to the amount of work that they must put in. Data Science needs hard work and requires a person to be thorough with his/her skills.

Due to several lucrative perks, Data Science is an attractive field. This, combined with the number of vacancies in Data Science makes it an untouched gold mine. Therefore, you should learn Data Science in order to enjoy a fruitful career.


In This Course, We Are Going To Work On 75 Real World Data Science, Machine Learning Projects Listed Below:

Project-1: Pan Card Tempering Detector App -Deploy On Heroku

Project-2: Dog breed prediction Flask App

Project-3: Image Watermarking App -Deploy On Heroku

Project-4: Traffic sign classification

Project-5: Text Extraction From Images Application

Project-6: Plant Disease Prediction Streamlit App

Project-7: Vehicle Detection And Counting Flask App

Project-8: Create A Face Swapping Flask App

Project-9: Bird Species Prediction Flask App

Project-10: Intel Image Classification Flask App


Project-11: Language Translator App Using IBM Cloud Service -Deploy On Heroku

Project-12: Predict Views On Advertisement Using IBM Watson -Deploy On Heroku

Project-13: Laptop Price Predictor -Deploy On Heroku

Project-14: WhatsApp Text Analyzer -Deploy On Heroku

Project-15: Course Recommendation System -Deploy On Heroku

Project-16: IPL Match Win Predictor -Deploy On Heroku

Project-17: Body Fat Estimator App -Deploy On Microsoft Azure

Project-18: Campus Placement Predictor App -Deploy On Microsoft Azure

Project-19: Car Acceptability Predictor -Deploy On Google Cloud

Project-20: Book Genre Classification App -Deploy On Amazon Web Services


Project 21 : DNA classification Deep Learning for finding E.Coli -AWS - Deploy On AWS

Project 22 : Predict the next word in a sentence. - AWS - Deploy On AWS

Project 23 : Predict Next Sequence of numbers using LSTM - AWS - Deploy On AWS

Project 24 : Keyword Extraction from text using NLP - Deploy On Azure

Project 25 : Correcting wrong spellings (correct spelling prediction) - Deploy On Azure

Project 26 : Music popularity classififcation - Deploy On Google App Engine

Project 27 : Advertisement Classification - Deploy On Google App Engine

Project 28 : Image Digit Classification - Deploy On AWS

Project 29 : Emotion Recognition using Neural Network - Deploy On AWS

Project 30 : Breast cancer Classification - Deploy On AWS


Project-31: Sentiment Analysis Django App -Deploy On Heroku

Project-32: Attrition Rate Django Application

Project-33: Find Legendary Pokemon Django App -Deploy On Heroku

Project-34: Face Detection Streamlit App

Project-35: Cats Vs Dogs Classification Flask App

Project-36: Customer Revenue Prediction App -Deploy On Heroku

Project-37: Gender From Voice Prediction App -Deploy On Heroku

Project-38: Restaurant Recommendation System

Project-39: Happiness Ranking Django App -Deploy On Heroku

Project-40: Forest Fire Prediction Django App -Deploy On Heroku


Project-41: Build Car Prices Prediction App -Deploy On Heroku

Project-42: Build Affair Count Django App -Deploy On Heroku

Project-43: Build Shrooming Predictions App -Deploy On Heroku

Project-44: Google Play App Rating prediction With Deployment On Heroku

Project-45: Build Bank Customers Predictions Django App -Deploy On Heroku

Project-46: Build Artist Sculpture Cost Prediction Django App -Deploy On Heroku

Project-47: Build Medical Cost Predictions Django App -Deploy On Heroku

Project-48: Phishing Webpages Classification Django App -Deploy On Heroku

Project-49: Clothing Fit-Size predictions Django App -Deploy On Heroku

Project-50: Build Similarity In-Text Django App -Deploy On Heroku


Project-51 : Sonic wave velocity prediction using Signal Processing Techniques

Project-52 : Estimation of Pore Pressure using Machine Learning

Project-53 : Audio processing using ML

Project-54 : Text characterisation using Speech recognition

Project-55 : Audio classification using Neural networks

Project-56 : Developing a voice assistant

Project-57 : Customer segmentation

Project-58 : FIFA 2019 Analysis

Project-59 : Sentiment analysis of web scrapped data

Project-60 : Determing Red Vine Quality


Project-61: Heart Attack Risk Prediction Using Eval ML (Auto ML)

Project-62: Credit Card Fraud Detection Using Pycaret (Auto ML)

Project-63: Flight Fare Prediction Using Auto SK Learn (Auto ML)

Project-64: Petrol Price Forecasting Using Auto Keras

Project-65: Bank Customer Churn Prediction Using H2O Auto ML

Project-66: Air Quality Index Predictor Using TPOT With End-To-End Deployment (Auto ML)

Project-67: Rain Prediction Using ML models & PyCaret With Deployment (Auto ML)

Project-68: Pizza Price Prediction Using ML And EVALML(Auto ML)

Project-69: IPL Cricket Score Prediction Using TPOT (Auto ML)

Project-70: Predicting Bike Rentals Count Using ML And H2O Auto ML


Project-71: Concrete Compressive Strength Prediction Using Auto Keras (Auto ML)

Project-72: Bangalore House Price Prediction Using Auto SK Learn (Auto ML)

Project-73: Hospital Mortality Prediction Using PyCaret (Auto ML)

Project-74: Employee Evaluation For Promotion Using ML And Eval Auto ML

Project-75: Drinking Water Potability Prediction Using ML And H2O Auto ML


The Only Course You Need To Become A Data Scientist, Get Hired And Start A New Career


Note (Read This): This Course Is Worth Of Your Time And Money, Enroll Now Before Offer Expires.

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76 sections

Introduction To The Course

3 lectures
Introduction
02:12
Udemy Course Outline
00:53
Udemy Course Feedback
00:14

Project-1: Build Pan Card Detector

8 lectures
Introduction
01:40
Loading libraries and dataset
03:49
Creating the pancard detector
12:18
Creating the Flask App
03:39
Creating Important functions
04:45
Deploy the app in Heroku
05:34
Testing the deployed pan card detector
01:46
Download the project files
00:01

Project-2: Build Dog Breed Prediction

8 lectures
Introduction
01:52
Importing the data and libraries
06:05
Data Preprocessing
03:00
Build and Train Model
06:57
Testing the model
02:18
Creating the Flask App
06:29
Running the app in system
04:02
Download the project files
00:01

Project-3: Image Watermarking App -Deploy On Heroku

6 lectures
Introduction
02:00
Importing libraries
02:40
Create text and image watermark
08:36
Creating the app
13:05
Deploying the app
05:18
Download The Project Files
00:01

Project-4: Traffic sign classification

6 lectures
Introduction
03:17
importing the data
05:45
Image processing
04:12
creating and testing the model
06:50
Creating model for test set
05:06
Download The Project Files
00:01

Project-5: Text Extraction From Images Application

7 lectures
Introduction
02:09
Importing libraries and data
03:35
Extracting the text from image
04:16
Modifying the extractor
07:47
Creating the extractor app
08:10
Running the extractor app
02:09
Download The Project Files
00:01

Project-6: Plant Disease Prediction Streamlit App

6 lectures
Introduction
03:49
Importing libraries and data
03:38
Understanding the data
04:56
Model building
07:23
Creating an app using streamlit
11:18
Download The Project Files
00:01

Project-7: Vehicle Detection And Counting Flask App

5 lectures
Introduction
03:01
Importing libraries and data
03:00
Transforming Images and creating output
10:43
Creating a Flask App
17:17
Download The Project Files
00:01

Project-8: Create A Face Swapping Flask App

5 lectures
Introduction
02:29
Importing libraries and data
04:22
Data preprocessing and creating output
13:59
Creating A Flask App
14:39
Download The Project Files
00:01

Project-9: Bird Species Prediction Flask App

6 lectures
Introduction to Bird Species Prediction
02:31
Importing Libraries And Data
06:04
Data processing
03:27
Creating ML Model
10:06
Creating A Flask App
13:17
Download The Project Files
00:01

Project-10: Intel Image Classification Flask App

5 lectures
Introduction
02:55
Importing and processing data
07:01
Creating a Model
08:44
Creating a Flask App
12:17
Download The Project Files
00:01

Project-11: Language Translator App Using IBM Cloud Service -Deploy On Heroku

6 lectures
Introduction
03:36
Setting Service
02:42
Integrating Service
08:22
Coding the UI
14:02
Deployment on Heroku
11:52
Download The Project Files
00:01

Project-12: Predict Views On Advertisement Using IBM Watson -Deploy On Heroku

8 lectures
Project Overview
02:24
Introduction
04:29
Setting up Watson Studio Part-1
09:33
Setting up Watson Studio Part-2
07:15
Deploying the Model on Deployment Center
05:01
Integrating Watson Service with UI
12:00
Deployment on Heroku Cloud
13:25
Download The Project Files
00:01

Project-13: Laptop Price Predictor -Deploy On Heroku

16 lectures
Overview
04:10
EDA Part-1
04:58
EDA Part-2
11:53
EDA Part-3
09:08
EDA Part-4
11:11
EDA Part-5
12:48
EDA Part-6
17:06
EDA Part-7
14:35
Model Building Part-1
20:24
Model Building Part-2
13:56
Model Building Part-3
15:16
Model Building Part-4
09:52
Model Building Part-5
02:10
Integrating with UI
15:23
Deployment on Heroku
09:36
Download The Project Files
00:01

Project-14: WhatsApp Text Analyzer -Deploy On Heroku

15 lectures
Introduction
06:25
Fetching Data from Whatsapp
02:38
Project Structure
07:36
Text Processing Part 1
11:08
Text Processing Part 2
14:36
Text Processing Part 3
05:54
Text Processing Part 4
14:11
Text Analytics Part 1
12:36
Text Analytics Part 2
10:32
Text Analytics Part 3
12:36
Text Analytics Part 4
12:12
Text Analytics Part 5
11:43
Text Analytics Part 6
07:56
Deployment on Heroku Cloud
10:37
Download The Project Files
00:01

Project-15: Course Recommendation System -Deploy On Heroku

7 lectures
Introduction
03:40
Coding Recommendation System
12:42
Integrating with Flask Server
14:49
Integrating Python Code with JavaScript
09:27
Exploratory Data Analysis
07:38
Deployment on Heroku Cloud
07:50
Download The Project Files
00:01

Project-16: IPL Match Win Predictor -Deploy On Heroku

9 lectures
Introduction
04:55
EDA Part 1
12:30
EDA Part 2
07:04
EDA Part 3
12:29
EDA Part 4
09:30
Model Building
14:43
Coding the UI
10:13
Deployment on Heroku Cloud
14:24
Download The Project Files
00:01

Project-17: Body Fat Estimator App -Deploy On Microsoft Azure

12 lectures
Introduction
03:48
EDA Part 1
08:55
EDA Part 2
11:09
Feature Selection Part 1
11:25
Feature Selection Part 2
05:28
Model Building
06:13
Model Evaluation
05:48
Coding the UI Part 1
10:09
Coding the UI Part 2
11:08
Model Deployment on Azure Part 1
12:43
Model Deployment on Azure Part 2
02:47
Download The Project Files
00:01

Project-18: Campus Placement Predictor App -Deploy On Microsoft Azure

13 lectures
Introduction
04:33
Data Preprocessing
09:30
EDA Part 1
10:26
EDA Part 2
07:56
Feature Selection
13:57
Model Building
05:08
Hyper Parameter Tuning, Model Testing
14:55
Coding the UI Part 1
06:22
Coding the UI Part 2
09:21
Coding the UI Part 3
12:40
Deployment Part 1
14:21
Deployment Part 2
02:00
Download The Project Files
00:01

Project-19: Car Acceptability Predictor -Deploy On Google Cloud

8 lectures
Introduction
04:54
Data Preprocessing
11:44
Model Building
08:31
Coding the UI
13:30
Integrating Jinja Framework
11:52
Integrating JavaScript with Flask
07:17
Deployment on GCP
16:46
Download The Project Files
00:01

Project-20: Book Genre Classification App -Deploy On Amazon Web Services

10 lectures
Introduction
03:35
Text Processing Part1
10:19
Text Processing Part2
10:29
Model Building
10:24
Model Testing
06:01
Integrating Model with Flask
11:11
Touch points on AWS
12:13
Deploying model on AWS EC2 instance
28:38
Fixing the Errors
03:07
Download The Project Files
00:01

Project 21 : DNA classification Deep Learning for finding E.Coli -AWS - Deploy O

11 lectures
Introduction to project
05:00
Understanding the libraries and dataset
11:58
Preprocessing the data
21:12
Building and training the model
11:02
Understanding MLP Classifier model
16:06
Understanding the Django framework
16:55
Running our Django application
13:39
Hosting on AWS
21:56
Hosting on AWS
12:04
Hosting on AWS
12:47
Download The Project Files
00:01

Project 22 : Predict the next word in a sentence. - AWS - Deploy On AWS

9 lectures
Introduction
04:03
Understanding about libraries and preprocessing dataset
11:43
Text tokenization and vectorization
17:02
Building and training the model
11:57
Django framework
10:50
Setting up the website and understanding the flow
18:04
Understanding the AWS cloud system
19:20
Setting up the server and hosting the website
20:40
Download The Project Files
00:01

Project 23 : Predict Next Sequence of numbers using LSTM - AWS - Deploy On AWS

8 lectures
Introduction
05:23
Understanding the libraries and dataset
12:36
Building and training the model
13:20
understanding the Django Framework
16:01
Working with the django framework to build the website
15:29
Instantiating the instance with ec2
15:05
Setting and running the server
26:36
Download The Project Files
00:01

Project 24 : Keyword Extraction from text using NLP - Deploy On Azure

8 lectures
Introduction
06:54
Introduction to libraries and data preprocessing
14:54
Developing the TF-IDF model
18:47
Understanding the django framework
15:20
Finalizing the website
14:07
Setting up the Azure VM
21:03
Setting and running the server
20:12
Download The Project Files
00:01

Project 25 : Correcting wrong spellings (correct spelling prediction) - Deploy O

8 lectures
Introduction
05:31
Brief of libraries and preprocessing
18:54
Developing the NLP model
15:43
Setting up the django application
14:33
Working on the django
13:31
Creating the VM instance on Azure
21:30
Setting up the VM for hosting
14:58
Download The Project Files
00:01

Project 26 : Music popularity classififcation - Deploy On Google App Engine

10 lectures
Introduction
03:53
Creating dataset through spotify API
15:51
Understanding the libraries and preprocessing the data
10:46
Developing the model
15:29
Setting up the django project
13:40
running our django application
14:07
Setting up the VM
10:04
Setting up the VM part-2
16:46
setting the code in VM
18:26
Download The Project Files
00:01

Project 27 : Advertisement Classification - Deploy On Google App Engine

10 lectures
Introduction
04:45
Understanding the libraries and the dataset
17:47
Understanding TF-IDF
12:12
Developing the LSTM model
11:19
Configuring the django project
16:39
Running the django application
13:06
Setting up the VM part-1
14:09
Setting up the VM part-2
11:26
Running the VM
14:41
Download The Project Files
00:01

Project 28 : Image Digit Classification - Deploy On AWS

8 lectures
Introduction
04:23
Creating and preprocessing the dataset
19:38
Building the baseline and CNN model
11:17
Setting up the django application
15:47
updating the website
15:51
Instantiating the VM
16:51
Setting the code inside the VM
14:44
Download The Project Files
00:01

Project 29 : Emotion Recognition using Neural Network - Deploy On AWS

8 lectures
Introduction
03:14
Understanding the libraries and model
12:29
Building and training the model
12:57
Setting up the django project
16:15
Running the django application
15:09
Setting up the VM
17:33
Running our code in the VM
17:25
Download The Project Files
00:01

Project 30 : Breast cancer Classification - Deploy On AWS

8 lectures
Introduction
05:21
Understanding the libraries and dataset
15:49
Developing the model
15:32
Setting up the django application
14:26
Running the django application
12:45
Setting up the VM
18:59
Running the VM
13:41
Download The Project Files
00:01

Project-31: Sentiment Analysis Django App -Deploy On Heroku

5 lectures
Introduction
02:08
Project Notebook Google Colab
18:31
Building Django App
10:55
Deploying App in heroku
12:36
Download The Project Files
00:01

Project-32: Attrition Rate Django Application

5 lectures
Introduction
02:27
Creating Colab Notebook
27:31
Creating Django App
10:59
Deploying App in heroku
09:52
Download The Project Files
00:01

Project-33: Find Legendary Pokemon Django App -Deploy On Heroku

5 lectures
Introduction
02:34
Creating Colab Notebook
20:00
Creating DJango App
12:34
Deploying App in heroku
09:02
Download The Project Files
00:01

Project-34: Face Detection Streamlit App

5 lectures
Introduction
02:44
Creating The Face App Using OpenCV
14:53
Creating The Face App Using OpenCV
10:15
Creating The Face App Using OpenCV
13:14
Download The Project Files
00:01

Project-35: Cats Vs Dogs Classification Flask App

6 lectures
Introduction
03:05
Creating Project Notebook
25:55
Building Model
08:45
Building Flask App
07:00
Building Flask App Deployment
09:54
Download The Project Files
00:01

Project-36: Customer Revenue Prediction App -Deploy On Heroku

5 lectures
Introduction
02:55
Colab Notebook
22:58
Creating Flask App
14:23
Deploying Flask App
09:16
Download The Project Files
00:01

Project-37: Gender From Voice Prediction App -Deploy On Heroku

5 lectures
Introduction
02:19
Creating Project Notebook
25:22
Creating Project App Django
12:46
Deploying The App
08:40
Download The Project Files
00:01

Project-38: Restaurant Recommendation System

5 lectures
Introduction
04:22
Creating Colab Notebook
14:05
Exploratory Data Analysis
10:38
Data Analysis2
31:57
Download The Project Files
00:01

Project-39: Happiness Ranking Django App -Deploy On Heroku

5 lectures
Introduction
03:27
Project Notebook
28:38
Creating Django App
17:36
Deploying Django
08:50
Download The Project Files
00:01

Project-40: Forest Fire Prediction Django App -Deploy On Heroku

6 lectures
Introduction
04:27
Project Notebook
25:53
Project Notebook Part2
08:22
Creating Django App
15:16
Deploying Django App
09:15
Download The Project Files
00:01

Project-41: Build Car Prices Prediction App -Deploy On Heroku

8 lectures
Introduction
02:40
Machine Learning model building part1
07:20
Machine Learning model building part2
11:53
Machine Learning model building part3
13:40
Creating Django Application part1
12:18
Creating Django Application part2
08:21
Deploying on Heroku
08:36
Download The Project Files
00:01

Project-42: Build Affair Count Django App -Deploy On Heroku

8 lectures
Introduction
03:07
Introductory Machine Learning model building
12:27
Feature Building and Selection
14:16
Model Building
05:40
Django Application Introduction
07:07
Django Application building
15:13
Deploying on Heroku
06:35
Download The Project Files
00:01

Project-43: Build Shrooming Predictions App -Deploy On Heroku

6 lectures
Introduction
02:57
Importing libraries and Understanding data
16:48
Building the model
09:57
Building Django Application
15:51
Deploying on Heroku
07:59
Download The Project Files
00:01

Project-44: Google Play App Rating prediction With Deployment On Heroku

7 lectures
Introduction
02:47
Introduction to libraries and dataset
14:56
Preprocessing the data
10:01
building the model
07:13
Django Application
14:57
Deploying to Heroku
07:17
Download The Project Files
00:01

Project-45: Build Bank Customers Predictions Django App -Deploy On Heroku

6 lectures
Introduction
03:07
Importing Libraries and understanding data
15:21
Building and training the model
13:08
Django Application
14:01
Deploying on heroku
07:21
Download The Project Files
00:01

Project-46: Build Artist Sculpture Cost Prediction Django App -Deploy On Heroku

6 lectures
Introduction
03:28
Understanding the data
13:34
Outliers and Model
17:15
Building Django Application
15:24
Deploying to Heroku
07:55
Download The Project Files
00:01

Project-47: Build Medical Cost Predictions Django App -Deploy On Heroku

6 lectures
Introduction
02:34
Introduction and handling the data
17:03
Building the model
06:17
Django Application
13:25
Heroku Deployment
06:36
Download The Project Files
00:01

Project-48: Phishing Webpages Classification Django App -Deploy On Heroku

6 lectures
Introduction
03:01
Understanding the data
14:00
Feature Selection and model building
09:18
Django Application
15:25
Deploying on Heroku
07:59
Download The Project Files
00:01

Project-49: Clothing Fit-Size predictions Django App -Deploy On Heroku

7 lectures
Introduction
03:46
Understanding the data
10:17
Cleaning the data
15:05
Building the model
10:09
Implementing Django Application
13:30
Deploying to heroku
07:39
Download The Project Files
00:01

Project-50: Build Similarity In-Text Django App -Deploy On Heroku

6 lectures
Introduction
05:40
Cleaning the data
12:29
Building the model
17:17
Implementing Django web application
16:25
Deploying to Heroku
09:04
Download The Project Files
00:01

Project-51 : Sonic wave velocity prediction using Signal Processing Techniques

8 lectures
Introduction to the project
06:15
Importing Libraries and DataSet
05:46
Data Analysis
08:19
Building ML Model
07:03
Evaluating ML Model
05:36
Performing Wavelet Transformation
11:34
Building and Evaluation of model with transformed data
06:56
Download The Project Files
00:01

Project-52 : Estimation of Pore Pressure using Machine Learning

7 lectures
Introduction to the project
07:26
Importing Libraries and Dataset
05:39
Data Analysis
08:24
Data Preprocessing
07:45
Building ML Models
11:51
Hyper tuning the models and results
09:08
Download The Project Files
00:01

Project-53 : Audio processing using ML

7 lectures
Introduction to the Project
05:27
Importing and reading Audio file
09:50
Extracting Time-Domain features-1
09:58
Extracting Time-Domain features-2
07:14
Fourier Transform and it_s applications-1
10:40
Fourier Transform and Frequency Domain features
06:45
Download The Project Files
00:01

Project-54 : Text characterisation using Speech recognition

5 lectures
Introduction to the Project
03:57
Importing Libraries and Audio Files.
04:45
Performing Speech Recognition
09:17
Performing Text Analysis
07:53
Download The Project Files
00:01

Project-55 : Audio classification using Neural networks

7 lectures
Introduction to the project
04:33
Importing Libraries and Audio Files
05:53
Extracting audio features 1
08:02
Extracting audio features 2
05:19
Model Development 1
04:27
Model Development 2
05:06
Download The Project Files
00:01

Project-56 : Developing a voice assistant

6 lectures
Introduction to the project
04:16
Importing Libraries
06:00
Writing Greet function
04:38
Writing Command function
05:10
Assigning tasks to the AI
11:37
Download The Project Files
00:01

Project-57 : Customer segmentation

6 lectures
Introduction to the Project
03:58
Importing Libraries and Dataset
03:58
Data Analysis
11:15
Data Preprocessing
07:07
Performing Clustering
08:14
Download The Project Files
00:01

Project-58 : FIFA 2019 Analysis

7 lectures
Introduction to the project
04:15
Importing Libraries and Dataset
04:26
Analysing Age Parameter-1
08:25
Analysing Age Parameter-2
06:56
Analysing Top Players
06:09
Finding Top skills and Building own team
05:13
Download The Project Files
00:01

Project-59 : Sentiment analysis of web scrapped data

6 lectures
Introduction to the Project
04:03
Importing Libraries and Dataset
06:20
Performing Web Scraping
11:23
Data Preprocessing
08:11
Performing Sentiment Analysis
10:06
Download The Project Files
00:01

Project-60 : Determing Red Vine Quality

6 lectures
Introduction to the Project
04:01
Importing Libraries
03:19
Data Analysis
09:12
Predicting quality using Labels
04:33
Classifying Good or Bad Wine
04:30
Download The Project Files
00:01

Project-61: Heart Attack Risk Prediction Using Eval ML (Auto ML)

7 lectures
Introduction to the Project
03:06
Importing Libraries and Datasets
02:24
Data Analysis
07:44
Model Building Part 1
06:15
Model Building Part 2
04:29
Model building and Predictions using Auto ML(Eval ML)
07:45
Download The Project Files
00:01

Project-62: Credit Card Fraud Detection Using Pycaret (Auto ML)

6 lectures
Introduction to the Project
04:41
Importing Libraries and DataSet
03:17
Data Analysis
07:02
Model Building using ML
07:42
Model Building and Prediction using PyCaret (AutoML)
10:20
Download The Project Files
00:01

Project-63: Flight Fare Prediction Using Auto SK Learn (Auto ML)

9 lectures
Introduction to the Project
04:07
Importing Libraries and DataSet
05:24
Data Analysis
05:30
Feature Engineering 1
05:44
Feature Engineering 2
06:42
Feature Selection
03:53
Model Building using ML
06:19
Model Building and Prediction using Auto SK Learn
05:48
Download The Project Files
00:01

Project-64: Petrol Price Forecasting Using Auto Keras

7 lectures
Introduction to the Project
05:03
Importing Libraries and Data Set
03:09
Data Analysis and splitting of Data
07:44
Data Preprocessing
05:56
Model Building and Prediction using LSTM model
03:57
Model Building and prediction using ARIMA and Auto Keras
05:24
Download The Project Files
00:01

Project-65: Bank Customer Churn Prediction Using H2O Auto ML

7 lectures
Introduction to the Project
06:06
Importing Libraries and Data Set
04:04
Data Analysis
11:48
Feature Engineering
07:32
Model Building and Prediction using ANN
05:43
Model Building and Prediction using H2O Auto ML (Auto ML)
11:11
Download The Project Files
00:01

Project-66: Air Quality Index Predictor Using TPOT With End-To-End Deployment (A

9 lectures
Introduction to the Project
05:50
Importing Libraries and Data sets
04:05
Data Analysis
09:44
Feature Engineering
05:26
Model Building using ML- 1
09:34
Model Building using ML- 2
05:30
Model Building and Predictions using TPOT Library
06:22
Deployment of Model using Flask API
11:15
Download The Project Files
00:01

Project-67: Rain Prediction Using ML models & PyCaret With Deployment (Auto ML)

10 lectures
Introduction to the Project
03:17
Importing Libraries and DataSet
05:46
Data Analysis and Handling Missing Values- 1
05:54
Data Analysis and Handling Missing Values- 2
06:48
Feature Engineering
08:38
Model Building using ML Algorithms
08:36
Model Building and Prediction using PyCaret (AutoML)
08:10
Using FLASK API
06:37
Deploying model using Heroku
05:19
Download The Project Files
00:01

Project-68: Pizza Price Prediction Using ML And EVALML(Auto ML)

7 lectures
Introduction to the project
04:26
Importing Libraries and DataSet
04:56
Data Analysis
10:00
Feature Engineering
06:17
Model Building using ML models
07:29
Model Building and Prediction using EVAL ML (Auto ML)
11:33
Download The Project Files
00:01

Project-69: IPL Cricket Score Prediction Using TPOT (Auto ML)

8 lectures
Introduction to the Project
05:02
Importing Libraries and DataSet
05:57
Data Analysis and Cleaning
07:10
Data Preprocessing
08:43
Model Building using ML Algorithms
08:50
Model Building using TPOT Auto ML Library-1
05:35
Model Building using TPOT Auto ML Library-2
03:32
Download The Project Files
00:01

Project-70: Predicting Bike Rentals Count Using ML And H2O Auto ML

9 lectures
Introduction to the Project
07:00
Importing libraries and DataSet
04:42
Data Analysis and Cleaning -1
10:00
Data Analysis and Cleaning -2
06:09
Data Preprocessing
03:46
Splitting the Data
03:37
Model Building and Prediction using ML
05:38
Model Building and Prediction using H2O Auto ML Library
08:40
Download The Project Files
00:01

Project-71: Concrete Compressive Strength Prediction Using Auto Keras (Auto ML)

7 lectures
Introduction to the Project
02:47
Importing Libraries and Data Set
03:13
Data Analysis
09:50
Feature Engineering
05:42
Model Building and Prediction using Deep Learning
05:47
Model Building and Prediction using Auto Keras(Auto ML)
08:22
Download The Project Files
00:01

Project-72: Bangalore House Price Prediction Using Auto SK Learn (Auto ML)

8 lectures
Introduction to the Project
03:16
Importing Libraries and DataSet
02:54
Data Analysis and Feature Engineering
06:20
Data Preprocessing 1
07:43
Data Preprocessing 2
04:34
Model Building and Prediction using ML
05:18
Model Building and Prediction using Auto SK Learn (Auto ML)
06:46
Download The Project Files
00:01

Project-73: Hospital Mortality Prediction Using PyCaret (Auto ML)

7 lectures
Introduction to the Project
04:19
Importing Libraries and DataSet
03:06
Data Analysis and Preprocessing 1
08:15
Data Analysis and Preprocessing 2
05:24
Model Building using ML
04:21
Model Building using Auto ML (PyCaret)
08:21
Download The Project Files
00:01

Project-74: Employee Evaluation For Promotion Using ML And Eval Auto ML

7 lectures
Introduction to the Project
02:51
Importing Libraries and DataSet
02:58
Data Analysis and Preprocessing 1
09:14
Data Analysis and Preprocessing 2
03:51
Model Building using ML
04:41
Model Building and Prediction using Eval Auto ML
08:53
Download The Project Files
00:01

Project-75: Drinking Water Potability Prediction Using ML And H2O Auto ML

7 lectures
Introduction to the Project
03:04
Importing Libraries and DataSet
03:13
Data Analysis
08:16
Feature Engineering
03:19
Model Building using ML
04:31
Model Building and Prediction using H2O Auto ML
08:24
Download The Project Files
00:01

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