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Packt Publishing - Deep Dive into Python Machine Learning
magnet:?xt=urn:btih:8d48ebb15a1af945bf781071adb6be1aa5602953&dn=Packt Publishing - Deep Dive into Python Machine Learning
磁力链接详情
Hash值:
8d48ebb15a1af945bf781071adb6be1aa5602953
点击数:
177
文件大小:
2.58 GB
文件数量:
187
创建日期:
2018-2-14 22:04
最后访问:
2024-6-28 09:48
访问标签:
Packt
Publishing
-
Deep
Dive
into
Python
Machine
Learning
文件列表详情
01 - The Course Overview.mp4 14.93 MB
02 - Python Basic Syntax and Block Structure.mp4 22.54 MB
03 - Built-in Data Structures and Comprehensions.mp4 17.79 MB
04 - First-Class Functions and Classes.mp4 12.33 MB
05 - Extensive Standard Library.mp4 31.14 MB
06 - New in Python 3.5.mp4 21.01 MB
07 - Downloading and Installing Python.mp4 15.34 MB
08 - Using the Command-Line and the Interactive Shell.mp4 7.1 MB
09 - Installing Packages with pip.mp4 11.04 MB
10 - Finding Packages in the Python Package Index.mp4 21.78 MB
100 - Compressing an Image Using Vector Quantization.mp4 16.33 MB
101 - Building a Mean Shift Clustering.mp4 11.26 MB
102 - Grouping Data Using Agglomerative Clustering.mp4 13.54 MB
103 - Evaluating the Performance of Clustering Algorithms.mp4 12.74 MB
104 - Automatically Estimating the Number of Clusters Using DBSCAN.mp4 14.94 MB
105 - Finding Patterns in Stock Market Data.mp4 11.34 MB
106 - Building a Customer Segmentation Model.mp4 9.78 MB
107 - Building Function Composition for Data Processing.mp4 13.67 MB
108 - Building Machine Learning Pipelines.mp4 15.17 MB
109 - Finding the Nearest Neighbors.mp4 8.05 MB
11 - Creating an Empty Package.mp4 11.59 MB
110 - Constructing a k-nearest Neighbors Classifier.mp4 19.77 MB
111 - Constructing a k-nearest Neighbors Regressor.mp4 9.75 MB
112 - Computing the Euclidean Distance Score.mp4 9.21 MB
113 - Computing the Pearson Correlation Score.mp4 8.32 MB
114 - Finding Similar Users in a Dataset.mp4 6.89 MB
115 - Generating Movie Recommendations.mp4 10.2 MB
116 - Preprocessing Data Using Tokenization.mp4 12.67 MB
117 - Stemming Text Data.mp4 8.77 MB
118 - Converting Text to Its Base Form Using Lemmatization.mp4 8.25 MB
119 - Dividing Text Using Chunking.mp4 7.42 MB
12 - Adding Modules to the Package.mp4 7.99 MB
120 - Building a Bag-of-Words Model.mp4 11.71 MB
121 - Building a Text Classifier.mp4 17.97 MB
122 - Identifying the Gender.mp4 10 MB
123 - Analyzing the Sentiment of a Sentence.mp4 14.39 MB
124 - Identifying Patterns in Text Using Topic Modelling.mp4 19.76 MB
125 - Reading and Plotting Audio Data.mp4 9.35 MB
126 - Transforming Audio Signals into the Frequency Domain.mp4 9.32 MB
127 - Generating Audio Signals with Custom Parameters.mp4 7.64 MB
128 - Synthesizing Music.mp4 9.81 MB
129 - Extracting Frequency Domain Features.mp4 8.13 MB
13 - Importing One of the Package's Modules from Another.mp4 9.29 MB
130 - Building Hidden Markov Models.mp4 9.6 MB
131 - Building a Speech Recognizer.mp4 12.94 MB
132 - Transforming Data into the Time Series Format.mp4 13.23 MB
133 - Slicing Time Series Data.mp4 5.32 MB
134 - Operating on Time Series Data.mp4 6.79 MB
135 - Extracting Statistics from Time Series.mp4 10.76 MB
136 - Building Hidden Markov Models for Sequential Data.mp4 17.7 MB
137 - Building Conditional Random Fields for Sequential Text Data.mp4 19.05 MB
138 - Analyzing Stock Market Data with Hidden Markov Models.mp4 11.84 MB
139 - Operating on Images Using OpenCV-Python.mp4 16.06 MB
14 - Adding Static Data Files to the Package.mp4 4.54 MB
140 - Detecting Edges.mp4 13.63 MB
141 - Histogram Equalization.mp4 11.46 MB
142 - Detecting Corners and SIFT Feature Points.mp4 16.86 MB
143 - Building a Star Feature Detector.mp4 7.35 MB
144 - Creating Features Using Visual Codebook and Vector Quantization.mp4 19.96 MB
145 - Training an Image Classifier Using Extremely Random Forests.mp4 11.41 MB
146 - Building an object recognizer.mp4 7.72 MB
147 - Capturing and Processing Video from a Webcam.mp4 6.95 MB
148 - Building a Face Detector using Haar Cascades.mp4 11.01 MB
149 - Building Eye and Nose Detectors.mp4 8.23 MB
15 - PEP 8 and Writing Readable Code.mp4 23.79 MB
150 - Performing Principal Component Analysis.mp4 7.98 MB
151 - Performing Kernel Principal Component Analysis.mp4 8.42 MB
152 - Performing Blind Source Separation.mp4 10.05 MB
153 - Building a Face Recognizer Using a Local Binary Patterns Histogram.mp4 20.53 MB
154 - Building a Perceptron.mp4 9.19 MB
155 - Building a Single-Layer Neural Network.mp4 5.93 MB
156 - Building a deep neural network.mp4 9.15 MB
157 - Creating a Vector Quantizer.mp4 8.36 MB
158 - Building a Recurrent Neural Network for Sequential Data Analysis.mp4 10.18 MB
159 - Visualizing the Characters in an Optical Character Recognition Database.mp4 5.17 MB
16 - Using Version Control.mp4 16.75 MB
160 - Building an Optical Character Recognizer Using Neural Networks.mp4 10.37 MB
161 - Plotting 3D Scatter plots.mp4 8.03 MB
162 - Plotting Bubble Plots.mp4 3.66 MB
163 - Animating Bubble Plots.mp4 9.43 MB
164 - Drawing Pie Charts.mp4 5.57 MB
165 - Plotting Date-Formatted Time Series Data.mp4 5.96 MB
166 - Plotting Histograms.mp4 3.67 MB
167 - Visualizing Heat Maps.mp4 4 MB
168 - Animating Dynamic Signals.mp4 6.79 MB
169 - The Course Overview.mp4 17.84 MB
17 - Using venv to Create a Stable and Isolated Work Area.mp4 8.15 MB
170 - What Is Deep Learning.mp4 7.37 MB
171 - Open Source Libraries for Deep Learning.mp4 21.33 MB
172 - Deep Learning Hello World! Classifying the MNIST Data.mp4 34.69 MB
173 - Introduction to Backpropagation.mp4 9.32 MB
174 - Understanding Deep Learning with Theano.mp4 19.26 MB
175 - Optimizing a Simple Model in Pure Theano.mp4 33.58 MB
176 - Keras Behind the Scenes.mp4 24.43 MB
177 - Fully Connected or Dense Layers.mp4 21.89 MB
178 - Convolutional and Pooling Layers.mp4 25.35 MB
179 - Large Scale Datasets, ImageNet, and Very Deep Neural Networks.mp4 20.32 MB
18 - Getting the Most Out of docstrings 1 - PEP 257 and docutils.mp4 38.58 MB
180 - Loading Pre-trained Models with Theano.mp4 23.52 MB
181 - Reusing Pre-trained Models in New Applications.mp4 31.83 MB
182 - Theano for Loops – the scan Module.mp4 19.47 MB
183 - Recurrent Layers.mp4 24.84 MB
184 - Recurrent Versus Convolutional Layers.mp4 6.58 MB
185 - Recurrent Networks –Training a Sentiment Analysis Model for Text.mp4 29.72 MB
186 - Bonus Challenge – Automatic Image Captioning.mp4 21.25 MB
187 - Captioning TensorFlow – Google's Machine Learning Library.mp4 21.61 MB
19 - Getting the Most Out of docstrings 2 - doctest.mp4 7.42 MB
20 - Making a Package Executable via python -m.mp4 9.19 MB
21 - Handling Command-Line Arguments with argparse.mp4 12.23 MB
22 - Interacting with the User.mp4 8.64 MB
23 - Executing Other Programs with Subprocess.mp4 45.53 MB
24 - Using Shell Scripts or Batch Files to Run Our Programs.mp4 4.62 MB
25 - Using concurrent.futures.mp4 46.73 MB
26 - Using Multiprocessing.mp4 21.9 MB
27 - Understanding Why This Isn't Like Parallel Processing.mp4 17.4 MB
28 - Using the asyncio Event Loop and Coroutine Scheduler.mp4 13.35 MB
29 - Waiting for Data to Become Available.mp4 6.66 MB
30 - Synchronizing Multiple Tasks.mp4 13.32 MB
31 - Communicating Across the Network.mp4 11.34 MB
32 - Using Function Decorators.mp4 12.98 MB
33 - Function Annotations.mp4 13.61 MB
34 - Class Decorators.mp4 11.44 MB
35 - Metaclasses.mp4 9.83 MB
36 - Context Managers.mp4 11.35 MB
37 - Descriptors.mp4 19.63 MB
38 - Understanding the Principles of Unit Testing.mp4 8.5 MB
39 - Using the unittest Package.mp4 17.13 MB
40 - Using unittest.mock.mp4 10.55 MB
41 - Using unittest's Test Discovery.mp4 9.72 MB
42 - Using Nose for Unified Test Discover and Reporting.mp4 11 MB
43 - What Does Reactive Programming Mean.mp4 4.82 MB
44 - Building a Simple Reactive Programming Framework.mp4 14.64 MB
45 - Using the Reactive Extensions for Python (RxPY).mp4 33.64 MB
46 - Microservices and the Advantages of Process Isolation.mp4 8.2 MB
47 - Building a High-Level Microservice with Flask.mp4 24.79 MB
48 - Building a Low-Level Microservice with nameko.mp4 12.78 MB
49 - Advantages and Disadvantages of Compiled Code.mp4 10.42 MB
50 - Accessing a Dynamic Library Using ctypes.mp4 14.92 MB
51 - Interfacing with C Code Using Cython.mp4 27.33 MB
52 - The Course Overview.mp4 9.69 MB
53 - Brief Introduction to Data Mining.mp4 8.59 MB
54 - Data Mining Basic Concepts and Applications.mp4 14.24 MB
55 - Why Python.mp4 5.22 MB
56 - Basics of Python.mp4 9.58 MB
57 - Installing IPython.mp4 3.88 MB
58 - Installing the Numpy Library.mp4 8.8 MB
59 - Installing the pandas Library.mp4 14.97 MB
60 - Installing Matplotlib.mp4 11.96 MB
61 - Installing scikit-learn.mp4 3.75 MB
62 - Data Cleaning.mp4 9.19 MB
63 - Data Preprocessing Techniques.mp4 8.41 MB
64 - Linear Regression Basic Model Approach.mp4 14.03 MB
65 - Evaluating Regression Models.mp4 9.14 MB
66 - Basic Regression Model Implementation to Predict House Prices.mp4 35.83 MB
67 - Regression Model Implementation to Predict Television Show Viewers.mp4 40.35 MB
68 - Logistic Regression.mp4 6.92 MB
69 - K – Nearest Neighbors Classifier.mp4 8.89 MB
70 - Support Vector Machine.mp4 9.4 MB
71 - Logistic Regression Model Implementation.mp4 47.17 MB
72 - K – Nearest Neighbor Classifier Implementation.mp4 38.31 MB
73 - Preprocessing Data Using Different Techniques.mp4 26.46 MB
74 - Label Encoding.mp4 10.54 MB
75 - Building a Linear Regressor.mp4 19.66 MB
76 - Regression Accuracy and Model Persistence.mp4 17.5 MB
77 - Building a Ridge Regressor.mp4 12.3 MB
78 - Building a Polynomial Regressor.mp4 11.43 MB
79 - Estimating housing prices.mp4 16.9 MB
80 - Computing relative importance of features.mp4 7.58 MB
81 - Estimating bicycle demand distribution.mp4 17.97 MB
82 - Building a Simple Classifier.mp4 12.21 MB
83 - Building a Logistic Regression Classifier.mp4 20.2 MB
84 - Building a Naive Bayes’ Classifier.mp4 8.74 MB
85 - Splitting the Dataset for Training and Testing.mp4 6.14 MB
86 - Evaluating the Accuracy Using Cross-Validation.mp4 8.21 MB
87 - Visualizing the Confusion Matrix and Extracting the Performance Report.mp4 15.79 MB
88 - Evaluating Cars based on Their Characteristics.mp4 23.16 MB
89 - Extracting Validation Curves.mp4 14.08 MB
90 - Extracting Learning Curves.mp4 7.31 MB
91 - Extracting the Income Bracket.mp4 15.04 MB
92 - Building a Linear Classifier Using Support Vector Machine.mp4 20.2 MB
93 - Building Nonlinear Classifier Using SVMs.mp4 8 MB
94 - Tackling Class Imbalance.mp4 13.3 MB
95 - Extracting Confidence Measurements.mp4 12.01 MB
96 - Finding Optimal Hyper-Parameters.mp4 10.42 MB
97 - Building an Event Predictor.mp4 16.95 MB
98 - Estimating Traffic.mp4 10.82 MB
99 - Clustering Data Using the k-means Algorithm.mp4 13.45 MB
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