Torrent Info
Title Packt Publishing - Deep Dive into Python Machine Learning
Category
Size 2.64GB

Files List
Please note that this page does not hosts or makes available any of the listed filenames. You cannot download any of those files from here.
01 - The Course Overview.mp4 14.93MB
02 - Python Basic Syntax and Block Structure.mp4 22.54MB
03 - Built-in Data Structures and Comprehensions.mp4 17.79MB
04 - First-Class Functions and Classes.mp4 12.33MB
05 - Extensive Standard Library.mp4 31.14MB
06 - New in Python 3.5.mp4 21.01MB
07 - Downloading and Installing Python.mp4 15.34MB
08 - Using the Command-Line and the Interactive Shell.mp4 7.10MB
09 - Installing Packages with pip.mp4 11.04MB
100 - Compressing an Image Using Vector Quantization.mp4 16.33MB
101 - Building a Mean Shift Clustering.mp4 11.26MB
102 - Grouping Data Using Agglomerative Clustering.mp4 13.54MB
103 - Evaluating the Performance of Clustering Algorithms.mp4 12.74MB
104 - Automatically Estimating the Number of Clusters Using DBSCAN.mp4 14.94MB
105 - Finding Patterns in Stock Market Data.mp4 11.34MB
106 - Building a Customer Segmentation Model.mp4 9.78MB
107 - Building Function Composition for Data Processing.mp4 13.67MB
108 - Building Machine Learning Pipelines.mp4 15.17MB
109 - Finding the Nearest Neighbors.mp4 8.05MB
10 - Finding Packages in the Python Package Index.mp4 21.78MB
110 - Constructing a k-nearest Neighbors Classifier.mp4 19.77MB
111 - Constructing a k-nearest Neighbors Regressor.mp4 9.75MB
112 - Computing the Euclidean Distance Score.mp4 9.21MB
113 - Computing the Pearson Correlation Score.mp4 8.32MB
114 - Finding Similar Users in a Dataset.mp4 6.89MB
115 - Generating Movie Recommendations.mp4 10.20MB
116 - Preprocessing Data Using Tokenization.mp4 12.67MB
117 - Stemming Text Data.mp4 8.77MB
118 - Converting Text to Its Base Form Using Lemmatization.mp4 8.25MB
119 - Dividing Text Using Chunking.mp4 7.42MB
11 - Creating an Empty Package.mp4 11.59MB
120 - Building a Bag-of-Words Model.mp4 11.71MB
121 - Building a Text Classifier.mp4 17.97MB
122 - Identifying the Gender.mp4 10.00MB
123 - Analyzing the Sentiment of a Sentence.mp4 14.39MB
124 - Identifying Patterns in Text Using Topic Modelling.mp4 19.76MB
125 - Reading and Plotting Audio Data.mp4 9.35MB
126 - Transforming Audio Signals into the Frequency Domain.mp4 9.32MB
127 - Generating Audio Signals with Custom Parameters.mp4 7.64MB
128 - Synthesizing Music.mp4 9.81MB
129 - Extracting Frequency Domain Features.mp4 8.13MB
12 - Adding Modules to the Package.mp4 7.99MB
130 - Building Hidden Markov Models.mp4 9.60MB
131 - Building a Speech Recognizer.mp4 12.94MB
132 - Transforming Data into the Time Series Format.mp4 13.23MB
133 - Slicing Time Series Data.mp4 5.32MB
134 - Operating on Time Series Data.mp4 6.79MB
135 - Extracting Statistics from Time Series.mp4 10.76MB
136 - Building Hidden Markov Models for Sequential Data.mp4 17.70MB
137 - Building Conditional Random Fields for Sequential Text Data.mp4 19.05MB
138 - Analyzing Stock Market Data with Hidden Markov Models.mp4 11.84MB
139 - Operating on Images Using OpenCV-Python.mp4 16.06MB
13 - Importing One of the Package's Modules from Another.mp4 9.29MB
140 - Detecting Edges.mp4 13.63MB
141 - Histogram Equalization.mp4 11.46MB
142 - Detecting Corners and SIFT Feature Points.mp4 16.86MB
143 - Building a Star Feature Detector.mp4 7.35MB
144 - Creating Features Using Visual Codebook and Vector Quantization.mp4 19.96MB
145 - Training an Image Classifier Using Extremely Random Forests.mp4 11.41MB
146 - Building an object recognizer.mp4 7.72MB
147 - Capturing and Processing Video from a Webcam.mp4 6.95MB
148 - Building a Face Detector using Haar Cascades.mp4 11.01MB
149 - Building Eye and Nose Detectors.mp4 8.23MB
14 - Adding Static Data Files to the Package.mp4 4.54MB
150 - Performing Principal Component Analysis.mp4 7.98MB
151 - Performing Kernel Principal Component Analysis.mp4 8.42MB
152 - Performing Blind Source Separation.mp4 10.05MB
153 - Building a Face Recognizer Using a Local Binary Patterns Histogram.mp4 20.53MB
154 - Building a Perceptron.mp4 9.19MB
155 - Building a Single-Layer Neural Network.mp4 5.93MB
156 - Building a deep neural network.mp4 9.15MB
157 - Creating a Vector Quantizer.mp4 8.36MB
158 - Building a Recurrent Neural Network for Sequential Data Analysis.mp4 10.18MB
159 - Visualizing the Characters in an Optical Character Recognition Database.mp4 5.17MB
15 - PEP 8 and Writing Readable Code.mp4 23.79MB
160 - Building an Optical Character Recognizer Using Neural Networks.mp4 10.37MB
161 - Plotting 3D Scatter plots.mp4 8.03MB
162 - Plotting Bubble Plots.mp4 3.66MB
163 - Animating Bubble Plots.mp4 9.43MB
164 - Drawing Pie Charts.mp4 5.57MB
165 - Plotting Date-Formatted Time Series Data.mp4 5.96MB
166 - Plotting Histograms.mp4 3.67MB
167 - Visualizing Heat Maps.mp4 4.00MB
168 - Animating Dynamic Signals.mp4 6.79MB
169 - The Course Overview.mp4 17.84MB
16 - Using Version Control.mp4 16.75MB
170 - What Is Deep Learning.mp4 7.37MB
171 - Open Source Libraries for Deep Learning.mp4 21.33MB
172 - Deep Learning Hello World! Classifying the MNIST Data.mp4 34.69MB
173 - Introduction to Backpropagation.mp4 9.32MB
174 - Understanding Deep Learning with Theano.mp4 19.26MB
175 - Optimizing a Simple Model in Pure Theano.mp4 33.58MB
176 - Keras Behind the Scenes.mp4 24.43MB
177 - Fully Connected or Dense Layers.mp4 21.89MB
178 - Convolutional and Pooling Layers.mp4 25.35MB
179 - Large Scale Datasets, ImageNet, and Very Deep Neural Networks.mp4 20.32MB
17 - Using venv to Create a Stable and Isolated Work Area.mp4 8.15MB
180 - Loading Pre-trained Models with Theano.mp4 23.52MB
181 - Reusing Pre-trained Models in New Applications.mp4 31.83MB
182 - Theano for Loops – the scan Module.mp4 19.47MB
183 - Recurrent Layers.mp4 24.84MB
184 - Recurrent Versus Convolutional Layers.mp4 6.58MB
185 - Recurrent Networks –Training a Sentiment Analysis Model for Text.mp4 29.72MB
186 - Bonus Challenge – Automatic Image Captioning.mp4 21.25MB
187 - Captioning TensorFlow – Google's Machine Learning Library.mp4 21.61MB
18 - Getting the Most Out of docstrings 1 - PEP 257 and docutils.mp4 38.58MB
19 - Getting the Most Out of docstrings 2 - doctest.mp4 7.42MB
20 - Making a Package Executable via python -m.mp4 9.19MB
21 - Handling Command-Line Arguments with argparse.mp4 12.23MB
22 - Interacting with the User.mp4 8.64MB
23 - Executing Other Programs with Subprocess.mp4 45.53MB
24 - Using Shell Scripts or Batch Files to Run Our Programs.mp4 4.62MB
25 - Using concurrent.futures.mp4 46.73MB
26 - Using Multiprocessing.mp4 21.90MB
27 - Understanding Why This Isn't Like Parallel Processing.mp4 17.40MB
28 - Using the asyncio Event Loop and Coroutine Scheduler.mp4 13.35MB
29 - Waiting for Data to Become Available.mp4 6.66MB
30 - Synchronizing Multiple Tasks.mp4 13.32MB
31 - Communicating Across the Network.mp4 11.34MB
32 - Using Function Decorators.mp4 12.98MB
33 - Function Annotations.mp4 13.61MB
34 - Class Decorators.mp4 11.44MB
35 - Metaclasses.mp4 9.83MB
36 - Context Managers.mp4 11.35MB
37 - Descriptors.mp4 19.63MB
38 - Understanding the Principles of Unit Testing.mp4 8.50MB
39 - Using the unittest Package.mp4 17.13MB
40 - Using unittest.mock.mp4 10.55MB
41 - Using unittest's Test Discovery.mp4 9.72MB
42 - Using Nose for Unified Test Discover and Reporting.mp4 11.00MB
43 - What Does Reactive Programming Mean.mp4 4.82MB
44 - Building a Simple Reactive Programming Framework.mp4 14.64MB
45 - Using the Reactive Extensions for Python (RxPY).mp4 33.64MB
46 - Microservices and the Advantages of Process Isolation.mp4 8.20MB
47 - Building a High-Level Microservice with Flask.mp4 24.79MB
48 - Building a Low-Level Microservice with nameko.mp4 12.78MB
49 - Advantages and Disadvantages of Compiled Code.mp4 10.42MB
50 - Accessing a Dynamic Library Using ctypes.mp4 14.92MB
51 - Interfacing with C Code Using Cython.mp4 27.33MB
52 - The Course Overview.mp4 9.69MB
53 - Brief Introduction to Data Mining.mp4 8.59MB
54 - Data Mining Basic Concepts and Applications.mp4 14.24MB
55 - Why Python.mp4 5.22MB
56 - Basics of Python.mp4 9.58MB
57 - Installing IPython.mp4 3.88MB
58 - Installing the Numpy Library.mp4 8.80MB
59 - Installing the pandas Library.mp4 14.97MB
60 - Installing Matplotlib.mp4 11.96MB
61 - Installing scikit-learn.mp4 3.75MB
62 - Data Cleaning.mp4 9.19MB
63 - Data Preprocessing Techniques.mp4 8.41MB
64 - Linear Regression Basic Model Approach.mp4 14.03MB
65 - Evaluating Regression Models.mp4 9.14MB
66 - Basic Regression Model Implementation to Predict House Prices.mp4 35.83MB
67 - Regression Model Implementation to Predict Television Show Viewers.mp4 40.35MB
68 - Logistic Regression.mp4 6.92MB
69 - K – Nearest Neighbors Classifier.mp4 8.89MB
70 - Support Vector Machine.mp4 9.40MB
71 - Logistic Regression Model Implementation.mp4 47.17MB
72 - K – Nearest Neighbor Classifier Implementation.mp4 38.31MB
73 - Preprocessing Data Using Different Techniques.mp4 26.46MB
74 - Label Encoding.mp4 10.54MB
75 - Building a Linear Regressor.mp4 19.66MB
76 - Regression Accuracy and Model Persistence.mp4 17.50MB
77 - Building a Ridge Regressor.mp4 12.30MB
78 - Building a Polynomial Regressor.mp4 11.43MB
79 - Estimating housing prices.mp4 16.90MB
80 - Computing relative importance of features.mp4 7.58MB
81 - Estimating bicycle demand distribution.mp4 17.97MB
82 - Building a Simple Classifier.mp4 12.21MB
83 - Building a Logistic Regression Classifier.mp4 20.20MB
84 - Building a Naive Bayes’ Classifier.mp4 8.74MB
85 - Splitting the Dataset for Training and Testing.mp4 6.14MB
86 - Evaluating the Accuracy Using Cross-Validation.mp4 8.21MB
87 - Visualizing the Confusion Matrix and Extracting the Performance Report.mp4 15.79MB
88 - Evaluating Cars based on Their Characteristics.mp4 23.16MB
89 - Extracting Validation Curves.mp4 14.08MB
90 - Extracting Learning Curves.mp4 7.31MB
91 - Extracting the Income Bracket.mp4 15.04MB
92 - Building a Linear Classifier Using Support Vector Machine.mp4 20.20MB
93 - Building Nonlinear Classifier Using SVMs.mp4 8.00MB
94 - Tackling Class Imbalance.mp4 13.30MB
95 - Extracting Confidence Measurements.mp4 12.01MB
96 - Finding Optimal Hyper-Parameters.mp4 10.42MB
97 - Building an Event Predictor.mp4 16.95MB
98 - Estimating Traffic.mp4 10.82MB
99 - Clustering Data Using the k-means Algorithm.mp4 13.45MB
Data Mining with Python- Implementing Classification and Regression.zip 16.77KB
Deep Learning with Python [Video].zip 590.78KB
Mastering Python - Second Edition [Video].zip 35.83KB
Python Machine Learning Solutions [Video].zip 57.83MB
Distribution statistics by country
Russia (RU) 4
United States (US) 2
Australia (AU) 1
Hungary (HU) 1
Ukraine (UA) 1
Denmark (DK) 1
Total 10
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