Udemy - TensorFlow 2.0 Masterclass: Hands-On Deep Learning and AI

  • Category Other
  • Type Tutorials
  • Language English
  • Total size 6.1 GB
  • Uploaded By tutsnode
  • Downloads 447
  • Last checked 2 weeks ago
  • Date uploaded 4 years ago
  • Seeders 13
  • Leechers 5

Infohash : 31A366991864CE5CD7DD490D093C74142F070B8B




Description

Google has recently released TensorFlow 2.0, it has so many features that simplify the Model Development, Maintenance, Processes and Performance…

Why TensorFlow 2.0 ?

Whether you’re an expert or a beginner, TensorFlow 2.0 is an end-to-end platform that makes it easy for you to build and deploy ML models

With the TensorFlow 2.0,

1) Building the Model is very Easy

2) Robust ML production anywhere

3) Powerful experimentation for research

With this course you will have the Complete Understanding of TensorFlow 2.0 from very Beginning !

List of the Projects,

Project 1: CNN for Digit Recognition

Project 2: CNN for Breast Cancer Detection

Project 3: CNN for Predicting the Bank Customer Satisfaction

Project 4: CNN for Credit Card Fraud Detection

Project 5: RNN – LSTM for IMDB Review Classification

Project 6: Google Stock Price Prediction with RNN and LSTM

Main Topics Covered in this Course,

Part 1: Introduction (Section 1)

Part 2: Artificial Neural Networks (Section 2 – Section 4)

Part 3: Convolutional Neural Networks (Section 5 – Section 11)

Part 4: Recurrent Neural Networks (Section 12 – Section 15)

Part 5: Transfer Learning

Part 6: Natural Language Processing (Section 16)

Part 7: Data Analysis with Numpy, Pandas and Data Visualization with Matplotlib (Section 17 – Section 19)

Regards,

Vijay Gadhave
Who this course is for:

Anyone who wants to start a career in the field of Data Science
Anyone Passionate about Deep Learning and Artificial Intelligence

Requirements

Python Programming Basics

Last Updated 1/2021

Files:

TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI [TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI 04 Binary Classification with Artificial Neural Networks
  • 014 Step 2 - Binary Classification.mp4 (168.9 MB)
  • 014 Step 2 - Binary Classification.en.srt (24.1 KB)
  • 013 Step 1 - Binary Classification.en.srt (2.9 KB)
  • 016 Step 4 - Binary Classification.en.srt (2.1 KB)
  • 015 Step 3 - Binary Classification.en.srt (10.6 KB)
  • 017 Step 5 - Binary Classification.en.srt (7.5 KB)
  • 015 Step 3 - Binary Classification.mp4 (63.2 MB)
  • 017 Step 5 - Binary Classification.mp4 (56.0 MB)
  • 013 Step 1 - Binary Classification.mp4 (21.3 MB)
  • 016 Step 4 - Binary Classification.mp4 (19.2 MB)
01 Welcome to the Course !
  • 001 Course Overview !.html (1.7 KB)
  • 003 Links to TensorFlow Notebooks.html (1.1 KB)
  • 002 Introduction to Google Colab.en.srt (5.5 KB)
  • 002 Introduction to Google Colab.mp4 (38.9 MB)
03 Building the Artificial Neural Networks (ANNs)
  • 009 Step 2 - Data Preprocessing.en.srt (21.2 KB)
  • 010 Step 3 - Building the Model.en.srt (10.8 KB)
  • 011 Step 4 - Training the Model.en.srt (10.2 KB)
  • 012 Step 5 - Model evaluation and performance.en.srt (9.7 KB)
  • 008 Step 1 - Installation and Setup.en.srt (4.8 KB)
  • 009 Step 2 - Data Preprocessing.mp4 (135.6 MB)
  • 012 Step 5 - Model evaluation and performance.mp4 (75.7 MB)
  • 010 Step 3 - Building the Model.mp4 (73.9 MB)
  • 011 Step 4 - Training the Model.mp4 (68.5 MB)
  • 008 Step 1 - Installation and Setup.mp4 (31.4 MB)
10 Project 3_ CNN for Predicting the Bank Customer Satisfaction
  • 037 CNN for Predicting the Bank Customer Satisfaction Part 2.en.srt (19.4 KB)
  • 038 CNN for Predicting the Bank Customer Satisfaction Part 3.en.srt (9.9 KB)
  • 036 CNN for Predicting the Bank Customer Satisfaction Part 1.en.srt (9.5 KB)
  • 037 CNN for Predicting the Bank Customer Satisfaction Part 2.mp4 (142.1 MB)
  • 039 CNN for Predicting the Bank Customer Satisfaction Part 4.en.srt (7.3 KB)
  • 038 CNN for Predicting the Bank Customer Satisfaction Part 3.mp4 (85.4 MB)
  • 036 CNN for Predicting the Bank Customer Satisfaction Part 1.mp4 (79.9 MB)
  • 039 CNN for Predicting the Bank Customer Satisfaction Part 4.mp4 (62.5 MB)
19 Annex 2_ Data Analysis with Pandas
  • 089 Pandas Operations.en.srt (9.4 KB)
  • 083 DataFrames Part 1.en.srt (14.0 KB)
  • 082 Pandas Series.en.srt (12.8 KB)
  • 084 DataFrames Part 2.en.srt (12.0 KB)
  • 085 DataFrames Part 3.en.srt (11.3 KB)
  • 088 Merging, Joining and Concatenating DataFrames.en.srt (9.7 KB)
  • 090 Reading and Writing Files in Pandas.en.srt (9.3 KB)
  • 087 Groupby Method.en.srt (9.0 KB)
  • 086 Missing Data.en.srt (7.9 KB)
  • 081 Pandas Introduction.en.srt (0.8 KB)
  • 083 DataFrames Part 1.mp4 (78.0 MB)
  • 082 Pandas Series.mp4 (70.0 MB)
  • 088 Merging, Joining and Concatenating DataFrames.mp4 (57.3 MB)
  • 085 DataFrames Part 3.mp4 (56.4 MB)
  • 084 DataFrames Part 2.mp4 (55.3 MB)
  • 087 Groupby Method.mp4 (49.1 MB)
  • 090 Reading and Writing Files in Pandas.mp4 (46.5 MB)
  • 089 Pandas Operations.mp4 (38.8 MB)
  • 086 Missing Data.mp4 (35.3 MB)
  • 081 Pandas Introduction.mp4 (12.5 MB)
02 Introduction to Artificial Neural Networks (ANNs)
  • 005 Activation Function.mp4 (156.6 MB)
  • 005 Activation Function.en.srt (9.5 KB)
  • 004 The Neuron.en.srt (6.6 KB)
  • 007 Gradient Descent and Back-Propagation.en.srt (4.5 KB)
  • 006 Cost Function.en.srt (3.0 KB)
  • 004 The Neuron.mp4 (102.1 MB)
  • 007 Gradient Descent and Back-Propagation.mp4 (75.0 MB)
  • 006 Cost Function.mp4 (51.7 MB)
15 Project 6_ Google Stock Price Prediction with RNN and LSTM
  • 056 Google Stock Price Prediction with RNN and LSTM Part 4.en.srt (17.8 KB)
  • 053 Google Stock Price Prediction with RNN and LSTM Part 1.en.srt (14.4 KB)
  • 055 Google Stock Price Prediction with RNN and LSTM Part 3.en.srt (11.9 KB)
  • 054 Google Stock Price Prediction with RNN and LSTM Part 2.en.srt (9.0 KB)
  • 057 Google Stock Price Prediction with RNN and LSTM Part 5.en.srt (3.3 KB)
  • 056 Google Stock Price Prediction with RNN and LSTM Part 4.mp4 (118.4 MB)
  • 053 Google Stock Price Prediction with RNN and LSTM Part 1.mp4 (110.2 MB)
  • 055 Google Stock Price Prediction with RNN and LSTM Part 3.mp4 (83.6 MB)
  • 054 Google Stock Price Prediction with RNN and LSTM Part 2.mp4 (54.6 MB)
  • 057 Google Stock Price Prediction with RNN and LSTM Part 5.mp4 (22.0 MB)
07 CNN for Binary Image Classification
  • 027 CNN for Binary Image Classification Step 3.en.srt (13.8 KB)
  • 028 CNN for Binary Image Classification Step 4.en.srt (10.7 KB)
  • 026 CNN for Binary Image Classification Step 2.en.srt (9.9 KB)
  • 025 CNN for Binary Image Classification Step 1.en.srt (2.3 KB)
  • 029 CNN for Binary Image Classification Step 5.en.srt (5.9 KB)
  • 027 CNN for Binary Image Classification Step 3.mp4 (95.3 MB)
  • 028 CNN for Binary Image Classification Step 4.mp4 (82.5 MB)
  • 026 CNN for Binary Image Classification Step 2.mp4 (80.4 MB)
  • 029 CNN for Binary Image Classification Step 5.mp4 (51.3 MB)
  • 025 CNN for Binary Image Classification Step 1.mp4 (16.6 MB)
17 Natural Language Processing
  • 072 Text Classification Part 1.en.srt (13.8 KB)
  • 073 Text Classification Part 2.en.srt (11.8 KB)
  • 068 Stop Words.en.srt (8.9 KB)
  • 065 Tokenization.en.srt (8.3 KB)
  • 066 Stemming.en.srt (7.7 KB)
  • 069 POS Tagging.en.srt (6.5 KB)
  • 070 Chunking.en.srt (6.4 KB)
  • 071 Named Entity Recognition.en.srt (6.3 KB)
  • 063 Introduction to Natural Language Processing.en.srt (4.5 KB)
  • 067 Lemmatization.en.srt (4.1 KB)
  • 064 NLTK Introduction and Installation.en.srt (3.4 KB)
  • 073 Text Classification Part 2.mp4 (140.0 MB)
  • 072 Text Classification Part 1.mp4 (131.0 MB)
  • 068 Stop Words.mp4 (98.5 MB)
  • 065 Tokenization.mp4 (86.8 MB)
  • 066 Stemming.mp4 (81.7 MB)
  • 069 POS Tagging.mp4 (74.4 MB)
  • 071 Named Entity Recognition.mp4 (68.5 MB)
  • 070 Chunking.mp4 (68.1 MB)
  • 063 Introduction to Natural Language Processing.mp4 (67.9 MB)
  • 067 Lemmatization.mp4 (31.5 MB)
  • 064 NLTK Introduction and Installation.mp4 (29.9 MB)
11 Project 4_ CNN for Credit Card Fraud Detection
  • 041 CNN for Credit Card Fraud Detection Part 2.en.srt (13.2 KB)
  • 042 CNN for Credit Card Fraud Detection Part 3.en.srt (11.5 KB)
  • 040 CNN for Credit Card Fraud Detection Part 1.en.srt (9.2 KB)
  • 043 CNN for Credit Card Fraud Detection Part 4.en.srt (7.7 KB)
  • 041 CNN for Credit Card Fraud Detection Part 2.mp4 (101.6 MB)
  • 042 CNN for Credit Card Fraud Detection Part 3.mp4 (91.0 MB)
  • 040 CNN for Credit Card Fraud Detection Part 1.mp4 (85.5 MB)
  • 043 CNN for Credit Card Fraud Detection Part 4.mp4 (61.7 MB)
06 Building Convolutional Neural Networks (CNNs)
  • 022 Building Convolutional Neural Network Step 3.en.srt (12.8 KB)
  • 020 Building Convolutional Neural Network Step 1.en.srt (1.5 KB)
  • 021 Building Convolutional Neural Network Step 2.en.srt (7.9 KB)
  • 024 Building Convolutional Neural Network Step 5.en.srt (7.5 KB)
  • 023 Building Convolutional Neural Network Step 4.en.srt (5.2 KB)
  • 022 Building Convolutional Neural Network Step 3.mp4 (128.6 MB)
  • 021 Building Convolutional Neural Network Step 2.mp4 (56.1 MB)
  • 024 Building Convolutional Neural Network Step 5.mp4 (47.7 MB)
  • 023 Building Convolutional Neural Network Step 4.mp4 (38.5 MB)
  • 020 Building Convolutional Neural Network Step 1.mp4 (10.7 MB)
20 Annex 3_ Data Visualization with Matplotlib
  • 091 Matplotlib Part 1 - Functional Method.en.srt (12.7 KB)
  • 096 Matplotlib Part 4.en.srt (11.1 KB)
  • 094 Matplotlib Part 2 - Figure size, Aspect ratio and DPI.en.srt (8.6 KB)
  • 092 Matplotlib Part 1 - Object Oriented Method.en.srt (7.6 KB)
  • 093 Matplotlib Part 2 - Subplots Method.en.srt (6.2 KB)
  • 095 Matplotlib Part 3.en.srt (6.1 KB)
  • 096 Matplotlib Part 4.mp4 (91.2 MB)
  • 091 Matplotlib Part 1 - Functional Method.mp4 (90.6 MB)
  • 094 Matplotlib Part 2 - Figure size, Aspect ratio and DPI.mp4 (53.9 MB)
  • 095 Matplotlib Part 3.mp4 (50.1 MB)
  • 092 Matplotlib Part 1 - Object Oriented Method.mp4 (44.0 MB)
  • 093 Matplotlib Part 2 - Subplots Method.mp4 (37.8 MB)
18 Annex 1_ Data Analysis with Numpy
  • 076 Numpy Arrays Part 2.en.srt (11.3 KB)
  • 078 Numpy Indexing and Selection Part 1.en.srt (8.7 KB)
  • 077 Numpy Arrays Part 3.en.srt (5.3 KB)
  • 079 Numpy Indexing and Selection Part 2.en.srt (5.3 KB)
  • 080 Numpy Operations.en.srt (4.2 KB)
  • 075 Numpy Arrays Part 1.en.srt (4.1 KB)
  • 074 Introduction to NumPy.en.srt (1.1 KB)
  • 076 Numpy Arrays Part 2.mp4 (54.0 MB)
  • 078 Numpy Indexing and Selection Part 1.mp4 (45.1 MB)
  • 080 Numpy Operations.mp4 (29.2 MB)
  • 077 Numpy Arrays Part 3.mp4 (27.3 MB)
  • 079 Numpy Indexing and Selection Part 2.mp4 (26.6 MB)
  • 075 Numpy Arrays Part 1.mp4 (16.8 MB)
  • 074 Introduction to NumPy.mp4 (16.3 MB)
09 Project 2_ CNN for Breast Cancer Detection
  • 033 CNN for Breast Cancer Detection Part 1.en.srt (11.1 KB)
  • 034 CNN for Breast Cancer Detection Part 2.en.srt (7.0 KB)
  • 035 CNN for Breast Cancer Detection Part 3.en.srt (5.2 KB)
  • 033 CNN for Breast Cancer Detection Part 1.mp4 (96.8 MB)
  • 034 CNN for Breast Cancer Detection Part 2.mp4 (56.9 MB)
  • 035 CNN for Breast Cancer Detection Part 3.mp4 (51.0 MB)
16 Transfer Learning
  • 059 Transfer Learning Part 1.en.srt (10.1 KB)
  • 061 Transfer Learning Part 3.en.srt (8.9 KB)
  • 060 Transfer Learning Part 2.en.srt (8.0 KB)
  • 062 Transfer Learning Part 4.en.srt (6.4 KB)
  • 058 Introduction to Transfer Learning.en.srt (3.7 KB)
  • 059 Transfer Learning Part 1.mp4 (80.2 MB)
  • 061 Transfer Learning Part 3.mp4 (76.4 MB)
  • 060 Transfer Learning Part 2.mp4 (57.9 MB)
  • 062 Transfer Learning Part 4.mp4 (47.7 MB)
  • 058 Introduction to Transfer Learning.mp4 (47.5 MB)
14 RNN - LSTM for Image Classification
  • 051 RNN - LSTM for Image Classification Part 2.en.srt (9.8 KB)
  • 052 RNN - LSTM for Image Classification Part 3.en.srt (8.3 KB)
  • 050 RNN - LSTM for Image Classification Part 1.en.srt (7.5 KB)
  • 051 RNN - LSTM for Image Classification Part 2.mp4 (78.5 MB)
  • 052 RNN - LSTM for Image Classification Part 3.mp4 (65.0 MB)
  • 050 RNN - LSTM for Image Classification Part 1.mp4 (53.7 MB)
08 Project 1_ CNN for Digit Recognition
  • 030 CNN for Digit Recognition Part 1.en.srt (9.8 KB)
  • 031 CNN for Digit Recognition Part 2.en.srt (7.8 KB)
  • 032 CNN for Digit Recognition Part 3.en.srt (7.3 KB)
  • 031 CNN for Digit Recognition Part 2.mp4 (64.3 MB)
  • 030 CNN for Digit Recognition Part 1.mp4 (64.1 MB)
  • 032 CNN for Digit Recognition Part 3.mp4 (62.6 MB)
13 Project 5_ RNN - LSTM for IMDB Review Classification
  • 049 RNN - LSTM for IMDB Review Classification Part 3.en.srt (8.1 KB)
  • 047 RNN - LSTM for IMDB Review Classification Part 1.en.srt (7.9 KB)
  • 048 RNN - LSTM for IMDB Review Classification Part 2.en.srt (7.6 KB)
  • 049 RNN - LSTM for IMDB Review Classification Part 3.mp4 (62.9 MB)
  • 047 RNN - LSTM for IMDB Review Classification Part 1.mp4 (58.6 MB)
  • 048 RNN - LSTM for IMDB Review Classification Part 2.mp4 (54.2 MB)
05 Introduction to Convolutional Neural Networks (CNNs)
  • 018 Convolutional Neural Network Part 1.en.srt (5.4 KB)
  • 019 Convolutional Neural Network Part 1.en.srt (4.8 KB)
  • 018 Convolutional Neural Network Part 1.mp4 (96.2 MB)
  • 019 Convolutional Neural Network Part 1.mp4 (81.1 MB)
12 Recurrent Neural Networks (RNNs)
  • 044 Introduction to Recurrent Neural Networks.en.srt (2.2 KB)
  • 045 Vanishing Gradient Problem.en.srt (2.4 KB)
  • 046 LSTM and GRU.en.srt (4.2 KB)
  • 046 LSTM and GRU.mp4 (59.9 MB)
  • 044 Introduction to Recurrent Neural Networks.mp4 (39.6 MB)
  • 045 Vanishing Gradient Problem.mp4 (39.1 MB)
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