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