Machine Learning & Deep Learning Projects for Beginners 2023

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Machine Learning & Deep Learning Projects for Beginners 2023 [TutsNode.net] - Machine Learning & Deep Learning Projects for Beginners 2023 2 - Project 1 Breast Cancer Detection
  • 6 - Data Preprocessing Part 2.mp4 (182.5 MB)
  • 9 - Hyperparameter Tuning using Randomized search.mp4 (171.0 MB)
  • 5 - Data Preprocessing Part 1.mp4 (133.1 MB)
  • 7 - Logistic Regression.mp4 (130.8 MB)
  • 8 - Random Forest Classifier.mp4 (60.8 MB)
  • 4 - Business Problem.mp4 (46.2 MB)
  • 10 - Predicting a Single Observation.mp4 (34.2 MB)
12 - Project 11 Multiclass image classification with ANN
  • 61 - Imp Lecture dont skip.html (2.7 KB)
  • 60 - Step 2 Data Preprocessing.mp4 (143.4 MB)
  • 64 - Step 5 Model evaluation and performance.mp4 (80.1 MB)
  • 62 - Step 3 Building the Model.mp4 (78.6 MB)
  • 63 - Step 4 Training the Model.mp4 (69.9 MB)
  • 59 - Step 1 Installation and Setup.mp4 (33.0 MB)
1 - Introduction
  • 3 - Colab Notebooks.html (0.3 KB)
  • 1 - Course Overview.mp4 (9.4 MB)
  • 2 - Important Udemy Review Update.mp4 (8.4 MB)
13 - Project 12 Binary Data Classification with ANN
  • 66 - Binary Data Classification Step 2.mp4 (171.4 MB)
  • 67 - Binary Data Classification Step 3.mp4 (67.4 MB)
  • 69 - Binary Data Classification Step 5.mp4 (56.8 MB)
  • 65 - Binary Data Classification Step 1.mp4 (22.3 MB)
  • 68 - Binary Data Classification Step 4.mp4 (20.4 MB)
5 - Project 4 House price prediction
  • 25 - Data Preprocessing Part 1.mp4 (159.2 MB)
  • 26 - Data Preprocessing Part 2.mp4 (143.3 MB)
  • 28 - Hyperparameter Tuning using Randomized Search.mp4 (111.0 MB)
  • 27 - Building and Finalizing the model.mp4 (92.5 MB)
  • 24 - Business Problem.mp4 (31.5 MB)
3 - Project 2 Customer churn rate prediction
  • 17 - Hyperparameter Tuning using Randomized Search.mp4 (153.6 MB)
  • 12 - Data Preprocessing part 1.mp4 (125.9 MB)
  • 13 - Data Preprocessing part 2.mp4 (104.5 MB)
  • 14 - Logistic Regression.mp4 (88.8 MB)
  • 15 - Random Forest Classifier.mp4 (47.1 MB)
  • 16 - XGBoost Classifier.mp4 (38.7 MB)
  • 11 - Business Problem.mp4 (33.3 MB)
  • 18 - Predicting a Single Observation.mp4 (27.5 MB)
18 - Project 17 Predicting the Bank Customer Satisfaction with CNN
  • 87 - Predicting the Bank Customer Satisfaction Step 2.mp4 (151.3 MB)
  • 88 - Predicting the Bank Customer Satisfaction Step 3.mp4 (90.9 MB)
  • 86 - Predicting the Bank Customer Satisfaction Step 1.mp4 (84.4 MB)
  • 89 - Predicting the Bank Customer Satisfaction Step 4.mp4 (63.4 MB)
24 - Project 23 Movie Review Classification with NLTK
  • 110 - Movie Review Classifivation with NLTK Step 2.mp4 (145.8 MB)
  • 109 - Movie Review Classifivation with NLTK Step 1.mp4 (134.8 MB)
14 - Project 13 Object Recognition in Images with CNN
  • 72 - Object Recognition in Images Step 3.mp4 (134.4 MB)
  • 71 - Object Recognition in Images Step 2.mp4 (59.6 MB)
  • 74 - Object Recognition in Images Step 5.mp4 (50.8 MB)
  • 73 - Object Recognition in Images Step 4.mp4 (41.0 MB)
  • 70 - Object Recognition in Images Step 1.mp4 (11.2 MB)
22 - Project 21 Google Stock Price Prediction with RNN and LSTM
  • 103 - Google Stock Price Prediction with RNN and LSTM Step 4.mp4 (120.3 MB)
  • 100 - Google Stock Price Prediction with RNN and LSTM Step 1.mp4 (117.1 MB)
  • 102 - Google Stock Price Prediction with RNN and LSTM Step 3.mp4 (85.3 MB)
  • 101 - Google Stock Price Prediction with RNN and LSTM Step 2.mp4 (58.1 MB)
  • 104 - Google Stock Price Prediction with RNN and LSTM Step 5.mp4 (23.5 MB)
7 - Project 6 Credit card fraud detection
  • 37 - Data Preprocessing Part 2.mp4 (113.2 MB)
  • 38 - Building and Finalizing the model.mp4 (91.8 MB)
  • 36 - Data Preprocessing Part 1.mp4 (47.7 MB)
  • 35 - Business Problem.mp4 (31.1 MB)
  • 39 - Predicting a single observation.mp4 (25.2 MB)
19 - Project 18 Credit Card Fraud Detection with CNN
  • 91 - Credit Card Fraud Detection with CNN Step 2.mp4 (107.8 MB)
  • 92 - Credit Card Fraud Detection with CNN Step 3.mp4 (96.7 MB)
  • 90 - Credit Card Fraud Detection with CNN Step 1.mp4 (90.4 MB)
  • 93 - Credit Card Fraud Detection with CNN Step 4.mp4 (62.8 MB)
6 - Project 5 E signing of customers based on financial data
  • 31 - Data Preprocessing Part 2.mp4 (107.4 MB)
  • 32 - Building and Finalizing the model.mp4 (92.6 MB)
  • 33 - Hyperparameter Tuning using Randomized Search.mp4 (89.4 MB)
  • 30 - Data Preprocessing Part 1.mp4 (82.1 MB)
  • 29 - Business Problem.mp4 (30.4 MB)
  • 34 - Predicting a single observation.mp4 (20.2 MB)
4 - Project 3 Medical insurance premium prediction
  • 21 - Data Preprocessing Part 2.mp4 (106.0 MB)
  • 22 - Building and Finalizing the model.mp4 (84.0 MB)
  • 20 - Data Preprocessing Part 1.mp4 (77.0 MB)
  • 23 - Predicting a single observation.mp4 (37.8 MB)
  • 19 - Business Problem.mp4 (19.3 MB)
17 - Project 16 Breast Cancer Detection with CNN
  • 83 - Breast Cancer Detection with CNN Step 1.mp4 (102.5 MB)
  • 84 - Breast Cancer Detection with CNN Step 2.mp4 (57.8 MB)
  • 85 - Breast Cancer Detection with CNN Step 3.mp4 (53.7 MB)
8 - Project 7 Employee Attrition Prediction
  • 44 - Hyperparameter Tuning using Randomized Search.mp4 (102.0 MB)
  • 42 - Data Preprocessing Part 2.mp4 (96.2 MB)
  • 41 - Data Preprocessing Part 1.mp4 (89.0 MB)
  • 43 - Building and Finalizing the model.mp4 (87.9 MB)
  • 40 - Business Problem.mp4 (25.4 MB)
  • 45 - Predicting a single observation.mp4 (13.7 MB)
15 - Project 14 Binary Image Classification with CNN
  • 77 - Binary Image Classification Step 3.mp4 (102.0 MB)
  • 78 - Binary Image Classification Step 4.mp4 (87.9 MB)
  • 76 - Binary Image Classification Step 2.mp4 (85.5 MB)
  • 79 - Binary Image Classification Step 5.mp4 (5

Description


Description

Hello Data Lover,

Welcome to this course, ‘Machine Learning & Deep Learning Projects for Beginners 2023’.

In this course, I will teach you to work on different 23 projects, which are from various categories like Regression, Classification, Clustering, ANN, CNN, RNN, and Transfer Learning!

Artificial Intelligence and Machine Learning are growing exponentially in today’s world. There is multiple application of AI and Deep Learning like Self Driving Cars, Chatbots, Image Recognition, Virtual Assistance, ALEXA, and so on…

With this course, you will understand the complexities of Machine Learning and Deep Learning in an easy way, as we will be working with Google colab Notebook.

In Google Colab you can start the coding with Zero Installation, whether you’re an expert or a beginner, in this course you will learn an end-to-end implementation of Machine Learning and Deep Learning Algorithms.

List of the Projects that you will work on,

Project 1: Breast Cancer Detection

Project 2: Customer churn rate prediction

Project 3: Medical insurance premium prediction

Project 4: House price prediction

Project 5: E signing of customers based on financial data

Project 6: Credit card fraud detection

Project 7: Employee Attrition Prediction

Project 8: Customer Segmentation

Project 9: Used Car Price Prediction

Project 10: Restaurant Reviews Classification

Project 11: Multiclass image classification with ANN

Project 12: Binary Data Classification with ANN

Project 13: Object Recognition in Images with CNN

Project 14: Binary Image Classification with CNN

Project 15: Digit Recognition with CNN

Project 16: Breast Cancer Detection with CNN

Project 17: Predicting the Bank Customer Satisfaction with CNN

Project 18: Credit Card Fraud Detection with CNN

Project 19: IMDB Review Classification with RNN – LSTM

Project 20: Multiclass Image Classification with RNN – LSTM

Project 21: Google Stock Price Prediction with RNN and LSTM

Project 22: Transfer Learning for Cats and Dogs Classification

Project 23: Movie Review Classification with NLTK

With this course, I will teach you:

1) To work on Regression, Classification, and Clustering Projects in Machine Learning

2) Text projects in Machine Learning

3) NN, CNN, RNN, and Transfer Learning Projects

4) To build the Neural Networks from the scratch

5) You will have a complete understanding of Artificial Neural Networks, Convolutional Neural Networks, and Recurrent Neural Networks

3) You will learn to build the neural networks with LSTM and GRU

4) Hands-On Transfer Learning

5) Learn Natural Language Processing by doing a text classification project

So what are you waiting for, Enroll Now and learn Machine Learning and Deep Learning to advance your career and increase your knowledge!

Regards,

Vijay Gadhave
Who this course is for:

Anyone who wants to learn practical applications of Machine Learning and Deep Learning

Requirements

Python Programming Basics
Basic understanding of Machine Learning and Deep Learning

Last Updated 11/2022



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Machine Learning & Deep Learning Projects for Beginners 2023

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seeders:77
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Machine Learning & Deep Learning Projects for Beginners 2023

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