FreeCoursesOnline Me PacktPub Master Deep Learning with TensorFlow in Python 2019 Video

FreeCoursesOnline Me PacktPub Master Deep Learning with TensorFlow in Python 2019 Video

Name	[FreeCoursesOnline.Me] PacktPub - Master Deep Learning with TensorFlow 2.0 in Python [2019] [Video]	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	2.5 GB
Total Files	89
Last Seen	2025-04-29 23:28
Hash	8EF76CBAB81900D4D663641CB4F159B74FBCB062

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/01.Welcome! Course introduction/
0101.Meet your instructors and why you should study machine learning.mp4	88.9 MB
0102.What does the course cover.mp4	41.0 MB
/02.Introduction to neural networks/
0201.Introduction to neural networks.mp4	48.0 MB
0202.Training the model.mp4	28.1 MB
0203.Types of machine learning.mp4	42.8 MB
0204.The linear model.mp4	27.3 MB
0205.The linear model. Multiple inputs.mp4	24.8 MB
0206.The linear model. Multiple inputs and multiple outputs.mp4	44.3 MB
0207.Graphical representation.mp4	23.0 MB
0208.The objective function.mp4	18.6 MB
0209.L2-norm loss.mp4	22.4 MB
0210.Cross-entropy loss.mp4	35.0 MB
0211.One parameter gradient descent.mp4	59.1 MB
0212.N-parameter gradient descent.mp4	60.4 MB
/03.Setting up the working environment/
0301.Setting up the environment - An introduction - Do not skip, please!.mp4	7.2 MB
0302.Why Python and why Jupyter.mp4	36.4 MB
0303.Installing Anaconda.mp4	32.9 MB
0304.The Jupyter dashboard - part 1.mp4	9.7 MB
0305.The Jupyter dashboard - part 2.mp4	21.4 MB
0306.Installing TensorFlow 2.mp4	53.7 MB
/04.Minimal example - your first machine learning algorithm/
0401.Minimal example - part 1.mp4	38.1 MB
0402.Minimal example - part 2.mp4	24.9 MB
0403.Minimal example - part 3.mp4	21.4 MB
0404.Minimal example - part 4.mp4	31.9 MB
/05.TensorFlow - An introduction/
0501.TensorFlow outline.mp4	44.0 MB
0502.TensorFlow 2 intro.mp4	39.7 MB
0503.A Note on Coding in TensorFlow.mp4	8.5 MB
0504.Types of file formats in TensorFlow and data handling.mp4	13.9 MB
0505.Model layout - inputs, outputs, targets, weights, biases, optimizer and loss.mp4	34.5 MB
0506.Interpreting the result and extracting the weights and bias.mp4	32.9 MB
0507.Customizing your model.mp4	22.7 MB
/06.Going deeper Introduction to deep neural networks/
0601.Layers.mp4	21.5 MB
0602.What is a deep net.mp4	34.2 MB
0603.Understanding deep nets in depth.mp4	61.0 MB
0604.Why do we need non-linearities.mp4	39.8 MB
0605.Activation functions.mp4	39.8 MB
0606.Softmax activation.mp4	26.2 MB
0607.Backpropagation.mp4	55.3 MB
0608.Backpropagation - visual representation.mp4	25.6 MB
/07.Overfitting/
0701.Underfitting and overfitting.mp4	35.7 MB
0702.Underfitting and overfitting - classification.mp4	34.1 MB
0703.Training and validation.mp4	39.3 MB
0704.Training, validation, and test.mp4	32.8 MB
0705.N-fold cross validation.mp4	26.8 MB
0706.Early stopping.mp4	29.7 MB
/08.Initialization/
0801.Initialization - Introduction.mp4	27.4 MB
0802.Types of simple initializations.mp4	12.9 MB
0803.Xavier initialization.mp4	20.1 MB
/09.Gradient descent and learning rates/
0901.Stochastic gradient descent.mp4	36.2 MB
0902.Gradient descent pitfalls.mp4	15.0 MB
0903.Momentum.mp4	19.9 MB
0904.Learning rate schedules.mp4	38.9 MB
0905.Learning rate schedules. A picture.mp4	11.5 MB
0906.Adaptive learning rate schedules.mp4	31.3 MB
0907.Adaptive moment estimation.mp4	30.5 MB
/10.Preprocessing/
1001.Preprocessing introduction.mp4	26.8 MB
1002.Basic preprocessing.mp4	11.6 MB
1003.Standardization.mp4	42.3 MB
1004.Dealing with categorical data.mp4	19.1 MB
1005.One-hot and binary encoding.mp4	33.8 MB
/11.The MNIST example/
1101.The dataset.mp4	21.8 MB
1102.How to tackle the MNIST.mp4	34.9 MB
1103.Importing the relevant packages and load the data.mp4	16.6 MB
1104.Preprocess the data - create a validation dataset and scale the data.mp4	28.4 MB
1105.Preprocess the data - shuffle and batch the data.mp4	38.4 MB
1106.Outline the model.mp4	28.7 MB
1107.Select the loss and the optimizer.mp4	13.3 MB
1108.Learning.mp4	21.4 MB
1109.Testing the model.mp4	16.0 MB
/12.Business case/
1201.Exploring the dataset and identifying predictors.mp4	31.6 MB
1202.Outlining the business case solution.mp4	10.0 MB
1203.Balancing the dataset.mp4	14.4 MB
1204.Preprocessing the data.mp4	46.7 MB
1205.Load the preprocessed data.mp4	19.1 MB
1206.Learning and interpreting the result.mp4	27.7 MB
1207.Setting an early stopping mechanism.mp4	22.5 MB
1208.Testing the model.mp4	10.1 MB
/13.Conclusion/
1301.See how much you have learned.mp4	40.8 MB
1302.What's further out there in the machine and deep learning world.mp4	18.4 MB
1303.An overview of CNNs.mp4	19.5 MB
1304.An overview of RNNs.mp4	28.7 MB
1305.An overview of non-NN approaches.mp4	42.1 MB
/Exercise Files/
exercise_files.zip	1.4 MB
Total files 89