本站已收录 番号和无损神作磁力链接/BT种子 

A Practical Guide to Machine Learning with TensorFlow 2.0 & Keras

种子简介

种子名称: A Practical Guide to Machine Learning with TensorFlow 2.0 & Keras
文件类型: 视频
文件数目: 43个文件
文件大小: 2.24 GB
收录时间: 2021-1-3 03:48
已经下载: 3
资源热度: 223
最近下载: 2024-9-13 15:49

下载BT种子文件

下载Torrent文件(.torrent) 立即下载

磁力链接下载

magnet:?xt=urn:btih:cfce7583a2de8c736cce05d12fa5956d43dd02bf&dn=A Practical Guide to Machine Learning with TensorFlow 2.0 & Keras 复制链接到迅雷、QQ旋风进行下载,或者使用百度云离线下载。

喜欢这个种子的人也喜欢

种子包含的文件

A Practical Guide to Machine Learning with TensorFlow 2.0 & Keras.torrent
  • 1. Introduction/1. Introduction.mp443.9MB
  • 1. Introduction/2. Jupyter Notebook & TensorFlow.mp449.82MB
  • 2. Machine Learning, Neural Networks & Deep Learning/1. Machine Learning Demo.mp458.33MB
  • 2. Machine Learning, Neural Networks & Deep Learning/10. Combining Neural Networks & AI.mp436.45MB
  • 2. Machine Learning, Neural Networks & Deep Learning/2. Deep Learning, Machine Learning, & Neural Networks Resources.mp424.26MB
  • 2. Machine Learning, Neural Networks & Deep Learning/3. Statistics & Machine Learning.mp422.53MB
  • 2. Machine Learning, Neural Networks & Deep Learning/4. Neurons & Neuron Layers.mp446.75MB
  • 2. Machine Learning, Neural Networks & Deep Learning/5. Deep Learning.mp440.46MB
  • 2. Machine Learning, Neural Networks & Deep Learning/6. Neurons & Model Training.mp447.2MB
  • 2. Machine Learning, Neural Networks & Deep Learning/7. Training Models.mp425.28MB
  • 2. Machine Learning, Neural Networks & Deep Learning/8. Deep Learning & AI.mp435.39MB
  • 2. Machine Learning, Neural Networks & Deep Learning/9. AI Modeling Demo.mp450.41MB
  • 3. Linear Regression/1. Jupyter Notebook Setup.mp432.92MB
  • 3. Linear Regression/2. Hardware & Compiler.mp425.35MB
  • 3. Linear Regression/3. Tensorflow Architecture.mp476.01MB
  • 3. Linear Regression/4. Plotting Uniform Data.mp432.82MB
  • 3. Linear Regression/5. Plotting Data with Noise.mp456.95MB
  • 3. Linear Regression/6. Predicting Data with TensorFlow.mp451.47MB
  • 3. Linear Regression/7. Visualizing Learning Rate & Loss.mp427.65MB
  • 3. Linear Regression/8. Learning Rate & Gradients.mp487.22MB
  • 3. Linear Regression/9. Learning Rate vs Steps.mp464.62MB
  • 4. Image Processing & Model Training/1. Image Processing with Keras.mp457.18MB
  • 4. Image Processing & Model Training/2. Creating a 2D Image Model.mp440.75MB
  • 4. Image Processing & Model Training/3. Sigmoid vs. ReLU.mp423.03MB
  • 4. Image Processing & Model Training/4. Softmax.mp418.72MB
  • 4. Image Processing & Model Training/5. Understanding the Model.mp454.55MB
  • 4. Image Processing & Model Training/6. Defining the Solver & Loss Function.mp467.61MB
  • 4. Image Processing & Model Training/7. Training a Model.mp4109.42MB
  • 4. Image Processing & Model Training/8. Comparing Different Models.mp477.06MB
  • 4. Image Processing & Model Training/9. Principal Component Analysis.mp461.65MB
  • 5. Convolution & Pooling/1. Convolutions & Pooling Definitions.mp445.15MB
  • 5. Convolution & Pooling/2. Adding Convolutions & Pooling.mp410.91MB
  • 5. Convolution & Pooling/3. Diagramming Convolutions & Pooling.mp4107.45MB
  • 5. Convolution & Pooling/4. Visualizing Convolutional Operations.mp475.14MB
  • 5. Convolution & Pooling/5. Predicting, Saving & Loading Models.mp468.04MB
  • 5. Convolution & Pooling/6. Neural Network Attention.mp4107.17MB
  • 5. Convolution & Pooling/7. Bias in Training Data Sets.mp431.65MB
  • 6. Text Analytics/1. Detecting Good & Bad Reviews.mp475.19MB
  • 6. Text Analytics/2. Natural Language Processing.mp492.96MB
  • 6. Text Analytics/3. Sentiment Analysis.mp466.21MB
  • 6. Text Analytics/4. Long Short Term Memory.mp480.95MB
  • 6. Text Analytics/5. Reinforcement Learning.mp481.51MB
  • 7. Wrapping Up/1. Wrapping Up.mp48.85MB