https://img87.pixhost.to/images/599/359020115_tuto.jpg
Download Free Download : Udemy TensorFlow for Deep Learning Bootcamp
mp4 | Video: h264,1280X720 | Audio: AAC, 44.1 KHz
Genre: eLearning | Language: English | Size: 31.9 GB
Files Included :
001 Course Outline.mp4 (60.45 MB)
MP4
002 Join Our Online Classroom!.mp4 (77.59 MB)
MP4
005 ZTM Resources.mp4 (43.82 MB)
MP4
001 What is deep learning.mp4 (36.22 MB)
MP4
002 Why use deep learning.mp4 (26.16 MB)
MP4
003 What are neural networks.mp4 (65.63 MB)
MP4
005 What is deep learning already being used for.mp4 (64.61 MB)
MP4
006 What is and why use TensorFlow.mp4 (69.29 MB)
MP4
007 What is a Tensor.mp4 (19.38 MB)
MP4
008 What we're going to cover throughout the course.mp4 (14.36 MB)
MP4
009 How to approach this course.mp4 (24.96 MB)
MP4
011 Creating your first tensors with TensorFlow and tf constant().mp4 (133.83 MB)
MP4
012 Creating tensors with TensorFlow and tf Variable().mp4 (59.2 MB)
MP4
013 Creating random tensors with TensorFlow.mp4 (88.82 MB)
MP4
014 Shuffling the order of tensors.mp4 (76.03 MB)
MP4
015 Creating tensors from NumPy arrays.mp4 (101.04 MB)
MP4
016 Getting information from your tensors (tensor attributes).mp4 (86.84 MB)
MP4
017 Indexing and expanding tensors.mp4 (85.73 MB)
MP4
018 Manipulating tensors with basic operations.mp4 (45.95 MB)
MP4
019 Matrix multiplication with tensors part 1.mp4 (103.39 MB)
MP4
020 Matrix multiplication with tensors part 2.mp4 (106.93 MB)
MP4
021 Matrix multiplication with tensors part 3.mp4 (80.48 MB)
MP4
022 Changing the datatype of tensors.mp4 (72.64 MB)
MP4
023 Tensor aggregation (finding the min, max, mean & more).mp4 (90.17 MB)
MP4
024 Tensor troubleshooting example (updating tensor datatypes).mp4 (70.68 MB)
MP4
025 Finding the positional minimum and maximum of a tensor (argmin and argmax).mp4 (97.68 MB)
MP4
026 Squeezing a tensor (removing all 1-dimension axes).mp4 (30.1 MB)
MP4
027 One-hot encoding tensors.mp4 (19.96 MB)
MP4
028 Trying out more tensor math operations.mp4 (57.17 MB)
MP4
029 Exploring TensorFlow and NumPy's compatibility.mp4 (43.6 MB)
MP4
030 Making sure our tensor operations run really fast on GPUs.mp4 (112.43 MB)
MP4
001 Introduction to Neural Network Regression with TensorFlow.mp4 (51.38 MB)
MP4
002 Inputs and outputs of a neural network regression model.mp4 (50.3 MB)
MP4
003 Anatomy and architecture of a neural network regression model.mp4 (51.87 MB)
MP4
004 Creating sample regression data (so we can model it).mp4 (89.43 MB)
MP4
006 The major steps in modelling with TensorFlow.mp4 (186.24 MB)
MP4
007 Steps in improving a model with TensorFlow part 1.mp4 (39.71 MB)
MP4
008 Steps in improving a model with TensorFlow part 2.mp4 (91.48 MB)
MP4
009 Steps in improving a model with TensorFlow part 3.mp4 (135.67 MB)
MP4
010 Evaluating a TensorFlow model part 1 (visualise, visualise, visualise).mp4 (66.92 MB)
MP4
011 Evaluating a TensorFlow model part 2 (the three datasets).mp4 (81.29 MB)
MP4
012 Evaluating a TensorFlow model part 3 (getting a model summary).mp4 (196.42 MB)
MP4
013 Evaluating a TensorFlow model part 4 (visualising a model's layers).mp4 (70.97 MB)
MP4
014 Evaluating a TensorFlow model part 5 (visualising a model's predictions).mp4 (66.57 MB)
MP4
015 Evaluating a TensorFlow model part 6 (common regression evaluation metrics).mp4 (70.81 MB)
MP4
016 Evaluating a TensorFlow regression model part 7 (mean absolute error).mp4 (56.52 MB)
MP4
017 Evaluating a TensorFlow regression model part 7 (mean square error).mp4 (32.6 MB)
MP4
018 Setting up TensorFlow modelling experiments part 1 (start with a simple model).mp4 (128 MB)
MP4
019 Setting up TensorFlow modelling experiments part 2 (increasing complexity).mp4 (61.4 MB)
MP4
020 Comparing and tracking your TensorFlow modelling experiments.mp4 (93.06 MB)
MP4
021 How to save a TensorFlow model.mp4 (93.26 MB)
MP4
022 How to load and use a saved TensorFlow model.mp4 (105.9 MB)
MP4
023 (Optional) How to save and download files from Google Colab.mp4 (68.94 MB)
MP4
024 Putting together what we've learned part 1 (preparing a dataset).mp4 (146.36 MB)
MP4
025 Putting together what we've learned part 2 (building a regression model).mp4 (122.94 MB)
MP4
026 Putting together what we've learned part 3 (improving our regression model).mp4 (156.78 MB)
MP4
027 Preprocessing data with feature scaling part 1 (what is feature scaling).mp4 (93.61 MB)
MP4
028 Preprocessing data with feature scaling part 2 (normalising our data).mp4 (83.12 MB)
MP4
029 Preprocessing data with feature scaling part 3 (fitting a model on scaled data).mp4 (76.74 MB)
MP4
001 Introduction to neural network classification in TensorFlow.mp4 (73.83 MB)
MP4
002 Example classification problems (and their inputs and outputs).mp4 (20.43 MB)
MP4
003 Input and output tensors of classification problems.mp4 (18.68 MB)
MP4
004 Typical architecture of neural network classification models with TensorFlow.mp4 (113.61 MB)
MP4
005 Creating and viewing classification data to model.mp4 (107.1 MB)
MP4
006 Checking the input and output shapes of our classification data.mp4 (38.9 MB)
MP4
007 Building a not very good classification model with TensorFlow.mp4 (127.17 MB)
MP4
008 Trying to improve our not very good classification model.mp4 (85.14 MB)
MP4
009 Creating a function to view our model's not so good predictions.mp4 (163.19 MB)
MP4
011 Make our poor classification model work for a regression dataset.mp4 (125.83 MB)
MP4
012 Non-linearity part 1 Straight lines and non-straight lines.mp4 (97.48 MB)
MP4
013 Non-linearity part 2 Building our first neural network with non-linearity.mp4 (60.23 MB)
MP4
014 Non-linearity part 3 Upgrading our non-linear model with more layers.mp4 (125.8 MB)
MP4
015 Non-linearity part 4 Modelling our non-linear data once and for all.mp4 (98.44 MB)
MP4
016 Non-linearity part 5 Replicating non-linear activation functions from scratch.mp4 (149 MB)
MP4
017 Getting great results in less time by tweaking the learning rate.mp4 (137.89 MB)
MP4
018 Using the TensorFlow History object to plot a model's loss curves.mp4 (62.92 MB)
MP4
019 Using callbacks to find a model's ideal learning rate.mp4 (156.68 MB)
MP4
020 Training and evaluating a model with an ideal learning rate.mp4 (89.55 MB)
MP4
021 Introducing more classification evaluation methods.mp4 (36.78 MB)
MP4
022 Finding the accuracy of our classification model.mp4 (33.87 MB)
MP4
023 Creating our first confusion matrix (to see where our model is getting confused).mp4 (56.54 MB)
MP4
024 Making our confusion matrix prettier.mp4 (114.96 MB)
MP4
025 Putting things together with multi-class classification part 1 Getting the data.mp4 (87.22 MB)
MP4
026 Multi-class classification part 2 Becoming one with the data.mp4 (48.8 MB)
MP4
027 Multi-class classification part 3 Building a multi-class classification model.mp4 (143.98 MB)
MP4
028 Multi-class classification part 4 Improving performance with normalisation.mp4 (114.43 MB)
MP4
029 Multi-class classification part 5 Comparing normalised and non-normalised data.mp4 (18.81 MB)
MP4
030 Multi-class classification part 6 Finding the ideal learning rate.mp4 (25.44 MB)
MP4
031 Multi-class classification part 7 Evaluating our model.mp4 (119.38 MB)
MP4
032 Multi-class classification part 8 Creating a confusion matrix.mp4 (34.22 MB)
MP4
033 Multi-class classification part 9 Visualising random model predictions.mp4 (58.93 MB)
MP4
034 What patterns is our model learning.mp4 (56.26 MB)
MP4
001 Introduction to Computer Vision with TensorFlow.mp4 (23.3 MB)
MP4
002 Introduction to Convolutional Neural Networks (CNNs) with TensorFlow.mp4 (77.91 MB)
MP4
003 Downloading an image dataset for our first Food Vision model.mp4 (73.2 MB)
MP4
004 Becoming One With Data.mp4 (45.67 MB)
MP4
005 Becoming One With Data Part 2.mp4 (90.2 MB)
MP4
006 Becoming One With Data Part 3.mp4 (33.74 MB)
MP4
007 Building an end to end CNN Model.mp4 (70.1 MB)
MP4
008 Using a GPU to run our CNN model 5x faster.mp4 (117.14 MB)
MP4
009 Trying a non-CNN model on our image data.mp4 (102.21 MB)
MP4
010 Improving our non-CNN model by adding more layers.mp4 (108.42 MB)
MP4
011 Breaking our CNN model down part 1 Becoming one with the data.mp4 (92.14 MB)
MP4
012 Breaking our CNN model down part 2 Preparing to load our data.mp4 (110 MB)
MP4
013 Breaking our CNN model down part 3 Loading our data with ImageDataGenerator.mp4 (105.23 MB)
MP4
014 Breaking our CNN model down part 4 Building a baseline CNN model.mp4 (87.47 MB)
MP4
015 Breaking our CNN model down part 5 Looking inside a Conv2D layer.mp4 (190.14 MB)
MP4
016 Breaking our CNN model down part 6 Compiling and fitting our baseline CNN.mp4 (64.91 MB)
MP4
017 Breaking our CNN model down part 7 Evaluating our CNN's training curves.mp4 (89.21 MB)
MP4
018 Breaking our CNN model down part 8 Reducing overfitting with Max Pooling.mp4 (132.37 MB)
MP4
019 Breaking our CNN model down part 9 Reducing overfitting with data augmentation.mp4 (66.34 MB)
MP4
020 Breaking our CNN model down part 10 Visualizing our augmented data.mp4 (160.58 MB)
MP4
021 Breaking our CNN model down part 11 Training a CNN model on augmented data.mp4 (96.01 MB)
MP4
022 Breaking our CNN model down part 12 Discovering the power of shuffling data.mp4 (105.23 MB)
MP4
023 Breaking our CNN model down part 13 Exploring options to improve our model.mp4 (42.39 MB)
MP4
024 Downloading a custom image to make predictions on.mp4 (44.31 MB)
MP4
025 Writing a helper function to load and preprocessing custom images.mp4 (107.27 MB)
MP4
026 Making a prediction on a custom image with our trained CNN.mp4 (100.93 MB)
MP4
027 Multi-class CNN's part 1 Becoming one with the data.mp4 (140.95 MB)
MP4
028 Multi-class CNN's part 2 Preparing our data (turning it into tensors).mp4 (46.62 MB)
MP4
029 Multi-class CNN's part 3 Building a multi-class CNN model.mp4 (91.9 MB)
MP4
030 Multi-class CNN's part 4 Fitting a multi-class CNN model to the data.mp4 (60.92 MB)
MP4
031 Multi-class CNN's part 5 Evaluating our multi-class CNN model.mp4 (34.31 MB)
MP4
032 Multi-class CNN's part 6 Trying to fix overfitting by removing layers.mp4 (131.54 MB)
MP4
033 Multi-class CNN's part 7 Trying to fix overfitting with data augmentation.mp4 (48.71 MB)
MP4
034 Multi-class CNN's part 8 Things you could do to improve your CNN model.mp4 (35.81 MB)
MP4
035 Multi-class CNN's part 9 Making predictions with our model on custom images.mp4 (97.9 MB)
MP4
036 Saving and loading our trained CNN model.mp4 (70.43 MB)
MP4
001 What is and why use transfer learning.mp4 (30.4 MB)
MP4
002 Downloading and preparing data for our first transfer learning model.mp4 (133.27 MB)
MP4
003 Introducing Callbacks in TensorFlow and making a callback to track our models.mp4 (95.32 MB)
MP4
004 Exploring the TensorFlow Hub website for pretrained models.mp4 (87.72 MB)
MP4
005 Building and compiling a TensorFlow Hub feature extraction model.mp4 (138.21 MB)
MP4
006 Blowing our previous models out of the water with transfer learning.mp4 (101.53 MB)
MP4
007 Plotting the loss curves of our ResNet feature extraction model.mp4 (62.18 MB)
MP4
008 Building and training a pre-trained EfficientNet model on our data.mp4 (108.05 MB)
MP4
009 Different Types of Transfer Learning.mp4 (113.32 MB)
MP4
010 Comparing Our Model's Results.mp4 (53.08 MB)
MP4
012 Exercise Imposter Syndrome.mp4 (8.97 MB)
MP4
001 Introduction to Transfer Learning in TensorFlow Part 2 Fine-tuning.mp4 (61.99 MB)
MP4
002 Importing a script full of helper functions (and saving lots of space).mp4 (54.49 MB)
MP4
003 Downloading and turning our images into a TensorFlow BatchDataset.mp4 (175.76 MB)
MP4
004 Discussing the four (actually five) modelling experiments we're running.mp4 (11.15 MB)
MP4
005 Comparing the TensorFlow Keras Sequential API versus the Functional API.mp4 (16.95 MB)
MP4
007 Creating our first model with the TensorFlow Keras Functional API.mp4 (134.12 MB)
MP4
008 Compiling and fitting our first Functional API model.mp4 (136.29 MB)
MP4
009 Getting a feature vector from our trained model.mp4 (149.28 MB)
MP4
010 Drilling into the concept of a feature vector (a learned representation).mp4 (53.28 MB)
MP4
011 Downloading and preparing the data for Model 1 (1 percent of training data).mp4 (98.15 MB)
MP4
012 Building a data augmentation layer to use inside our model.mp4 (118.18 MB)
MP4
014 Visualizing what happens when images pass through our data augmentation layer.mp4 (123.3 MB)
MP4
015 Building Model 1 (with a data augmentation layer and 1% of training data).mp4 (155.92 MB)
MP4
016 Building Model 2 (with a data augmentation layer and 10% of training data).mp4 (161.1 MB)
MP4
017 Creating a ModelCheckpoint to save our model's weights during training.mp4 (68.95 MB)
MP4
018 Fitting and evaluating Model 2 (and saving its weights using ModelCheckpoint).mp4 (69.29 MB)
MP4
019 Loading and comparing saved weights to our existing trained Model 2.mp4 (63.03 MB)
MP4
020 Preparing Model 3 (our first fine-tuned model).mp4 (201.27 MB)
MP4
021 Fitting and evaluating Model 3 (our first fine-tuned model).mp4 (59.53 MB)
MP4
022 Comparing our model's results before and after fine-tuning.mp4 (84.75 MB)
MP4
023 Downloading and preparing data for our biggest experiment yet (Model 4).mp4 (56.64 MB)
MP4
024 Preparing our final modelling experiment (Model 4).mp4 (96.11 MB)
MP4
025 Fine-tuning Model 4 on 100% of the training data and evaluating its results.mp4 (98.02 MB)
MP4
026 Comparing our modelling experiment results in TensorBoard.mp4 (96.09 MB)
MP4
027 How to view and delete previous TensorBoard experiments.mp4 (18.48 MB)
MP4
001 Introduction to Transfer Learning Part 3 Scaling Up.mp4 (40.99 MB)
MP4
002 Getting helper functions ready and downloading data to model.mp4 (132.57 MB)
MP4
003 Outlining the model we're going to build and building a ModelCheckpoint callback.mp4 (29.17 MB)
MP4
004 Creating a data augmentation layer to use with our model.mp4 (36.19 MB)
MP4
005 Creating a headless EfficientNetB0 model with data augmentation built in.mp4 (81.39 MB)
MP4
006 Fitting and evaluating our biggest transfer learning model yet.mp4 (60.1 MB)
MP4
007 Unfreezing some layers in our base model to prepare for fine-tuning.mp4 (100.48 MB)
MP4
008 Fine-tuning our feature extraction model and evaluating its performance.mp4 (66.14 MB)
MP4
009 Saving and loading our trained model.mp4 (57.96 MB)
MP4
010 Downloading a pretrained model to make and evaluate predictions with.mp4 (80.12 MB)
MP4
011 Making predictions with our trained model on 25,250 test samples.mp4 (115.71 MB)
MP4
012 Unravelling our test dataset for comparing ground truth labels to predictions.mp4 (38.11 MB)
MP4
013 Confirming our model's predictions are in the same order as the test labels.mp4 (50.88 MB)
MP4
014 Creating a confusion matrix for our model's 101 different classes.mp4 (162.54 MB)
MP4
015 Evaluating every individual class in our dataset.mp4 (133.35 MB)
MP4
016 Plotting our model's F1-scores for each separate class.mp4 (78.45 MB)
MP4
017 Creating a function to load and prepare images for making predictions.mp4 (109.08 MB)
MP4
018 Making predictions on our test images and evaluating them.mp4 (173.5 MB)
MP4
019 Discussing the benefits of finding your model's most wrong predictions.mp4 (59.09 MB)
MP4
020 Writing code to uncover our model's most wrong predictions.mp4 (110.89 MB)
MP4
021 Plotting and visualising the samples our model got most wrong.mp4 (127.93 MB)
MP4
022 Making predictions on and plotting our own custom images.mp4 (110.03 MB)
MP4
001 Introduction to Milestone Project 1 Food Vision Big™.mp4 (28.07 MB)
MP4
002 Making sure we have access to the right GPU for mixed precision training.mp4 (87.85 MB)
MP4
003 Getting helper functions ready.mp4 (26.5 MB)
MP4
004 Introduction to TensorFlow Datasets (TFDS).mp4 (99.42 MB)
MP4
005 Exploring and becoming one with the data (Food101 from TensorFlow Datasets).mp4 (116.54 MB)
MP4
006 Creating a preprocessing function to prepare our data for modelling.mp4 (132.52 MB)
MP4
007 Batching and preparing our datasets (to make them run fast).mp4 (133.48 MB)
MP4
008 Exploring what happens when we batch and prefetch our data.mp4 (55.73 MB)
MP4
009 Creating modelling callbacks for our feature extraction model.mp4 (60.3 MB)
MP4
011 Turning on mixed precision training with TensorFlow.mp4 (109.41 MB)
MP4
012 Creating a feature extraction model capable of using mixed precision training.mp4 (108.39 MB)
MP4
013 Checking to see if our model is u