[08-2020] python-data-science-machine-learning-bootcamp

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[08-2020] python-data-science-machine-learning-bootcamp的二维码

文档列表

04 Introduction to Optimisation and the Gradient Descent Algorithm/036 [Python] - Loops and the Gradient Descent Algorithm.mp4 471.0 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/037 [Python] - Advanced Functions and the Pitfalls of Optimisation (Part 1).mp4 468.5 MB
12 Serving a Tensorflow Model through a Website/198 Introduction to OpenCV.mp4 453.3 MB
12 Serving a Tensorflow Model through a Website/200 Calculating the Centre of Mass and Shifting the Image.mp4 425.6 MB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/169 Model Evaluation and the Confusion Matrix.mp4 384.2 MB
03 Python Programming for Data Science and Machine Learning/021 [Python] - Module Imports.mp4 366.5 MB
11 Use Tensorflow to Classify Handwritten Digits/183 Different Model Architectures_ Experimenting with Dropout.mp4 352.1 MB
05 Predict House Prices with Multivariable Linear Regression/068 Working with Seaborn Pairplots & Jupyter Microbenchmarking Techniques.mp4 350.7 MB
12 Serving a Tensorflow Model through a Website/193 Loading a Tensorflow.js Model and Starting your own Server.mp4 336.9 MB
12 Serving a Tensorflow Model through a Website/195 Styling an HTML Canvas.mp4 327.6 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/038 [Python] - Tuples and the Pitfalls of Optimisation (Part 2).mp4 317.0 MB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/167 Use the Model to Make Predictions.mp4 314.6 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/040 How to Create 3-Dimensional Charts.mp4 308.6 MB
12 Serving a Tensorflow Model through a Website/196 Drawing on an HTML Canvas.mp4 305.1 MB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/166 Use Regularisation to Prevent Overfitting_ Early Stopping & Dropout Techniques.mp4 301.0 MB
12 Serving a Tensorflow Model through a Website/199 Resizing and Adding Padding to Images.mp4 300.2 MB
12 Serving a Tensorflow Model through a Website/202 Adding the Game Logic.mp4 299.9 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/039 Understanding the Learning Rate.mp4 294.2 MB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/141 Visualising the Decision Boundary.mp4 290.8 MB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/146 A Naive Bayes Implementation using SciKit Learn.mp4 283.7 MB
03 Python Programming for Data Science and Machine Learning/026 How to Make Sense of Python Documentation for Data Visualisation.mp4 277.9 MB
03 Python Programming for Data Science and Machine Learning/027 Working with Python Objects to Analyse Data.mp4 271.4 MB
12 Serving a Tensorflow Model through a Website/192 HTML and CSS Styling.mp4 256.5 MB
09 Introduction to Neural Networks and How to Use Pre-Trained Models/150 Layers, Feature Generation and Learning.mp4 248.7 MB
03 Python Programming for Data Science and Machine Learning/025 [Python] - Objects - Understanding Attributes and Methods.mp4 245.9 MB
05 Predict House Prices with Multivariable Linear Regression/077 Model Simplification & Baysian Information Criterion.mp4 240.6 MB
05 Predict House Prices with Multivariable Linear Regression/081 Making Predictions (Part 1)_ MSE & R-Squared.mp4 228.4 MB
05 Predict House Prices with Multivariable Linear Regression/058 Clean and Explore the Data (Part 2)_ Find Missing Values.mp4 218.0 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/043 [Python] - Loops and Performance Considerations.mp4 215.6 MB
11 Use Tensorflow to Classify Handwritten Digits/177 Creating Tensors and Setting up the Neural Network Architecture.mp4 215.1 MB
03 Python Programming for Data Science and Machine Learning/020 [Python & Pandas] - Dataframes and Series.mp4 213.5 MB
07 Train a Naive Bayes Classifier to Create a Spam Filter_ Part 2/129 Create a Full Matrix.mp4 210.2 MB
05 Predict House Prices with Multivariable Linear Regression/083 Build a Valuation Tool (Part 1)_ Working with Pandas Series & Numpy ndarrays.mp4 208.1 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/098 [Python] - Generator Functions & the yield Keyword.mp4 207.3 MB
05 Predict House Prices with Multivariable Linear Regression/061 Working with Index Data, Pandas Series, and Dummy Variables.mp4 205.1 MB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/164 Interacting with the Operating System and the Python Try-Catch Block.mp4 203.1 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/041 Understanding Partial Derivatives and How to use SymPy.mp4 202.7 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/100 Cleaning Data (Part 1)_ Check for Empty Emails & Null Entries.mp4 201.2 MB
12 Serving a Tensorflow Model through a Website/188 Saving Tensorflow Models.mp4 201.1 MB
05 Predict House Prices with Multivariable Linear Regression/065 Visualising Correlations with a Heatmap.mp4 200.8 MB
03 Python Programming for Data Science and Machine Learning/023 [Python] - Functions - Part 2_ Arguments & Parameters.mp4 198.9 MB
02 Predict Movie Box Office Revenue with Linear Regression/008 Explore & Visualise the Data with Python.mp4 197.9 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/089 Gathering Email Data and Working with Archives & Text Editors.mp4 195.9 MB
11 Use Tensorflow to Classify Handwritten Digits/180 Tensorboard Summaries and the Filewriter.mp4 195.6 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/115 Styling the Word Cloud with a Mask.mp4 193.6 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/117 Styling Word Clouds with Custom Fonts.mp4 193.1 MB
12 Serving a Tensorflow Model through a Website/201 Making a Prediction from a Digit drawn on the HTML Canvas.mp4 190.6 MB
09 Introduction to Neural Networks and How to Use Pre-Trained Models/154 Making Predictions using InceptionResNet.mp4 190.0 MB
05 Predict House Prices with Multivariable Linear Regression/080 Residual Analysis (Part 2)_ Graphing and Comparing Regression Residuals.mp4 186.9 MB
12 Serving a Tensorflow Model through a Website/190 Converting a Model to Tensorflow.js.mp4 179.9 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/093 Joint & Conditional Probability.mp4 177.5 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/044 Reshaping and Slicing N-Dimensional Arrays.mp4 176.5 MB
05 Predict House Prices with Multivariable Linear Regression/085 Build a Valuation Tool (Part 3)_ Docstrings & Creating your own Python Module.mp4 176.1 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/108 Removing HTML tags with BeautifulSoup.mp4 175.6 MB
11 Use Tensorflow to Classify Handwritten Digits/181 Understanding the Tensorflow Graph_ Nodes and Edges.mp4 175.5 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/096 Reading Files (Part 2)_ Stream Objects and Email Structure.mp4 175.5 MB
05 Predict House Prices with Multivariable Linear Regression/076 Understanding VIF & Testing for Multicollinearity.mp4 172.6 MB
11 Use Tensorflow to Classify Handwritten Digits/184 Prediction and Model Evaluation.mp4 170.2 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/122 Sparse Matrix (Part 2)_ Data Munging with Nested Loops.mp4 168.3 MB
05 Predict House Prices with Multivariable Linear Regression/084 [Python] - Conditional Statements - Build a Valuation Tool (Part 2).mp4 167.6 MB
09 Introduction to Neural Networks and How to Use Pre-Trained Models/155 Coding Challenge Solution_ Using other Keras Models.mp4 162.5 MB
05 Predict House Prices with Multivariable Linear Regression/064 Calculating Correlations and the Problem posed by Multicollinearity.mp4 162.4 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/114 Creating your First Word Cloud.mp4 160.0 MB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/161 Exploring the CIFAR Data.mp4 158.4 MB
05 Predict House Prices with Multivariable Linear Regression/066 Techniques to Style Scatter Plots.mp4 157.3 MB
05 Predict House Prices with Multivariable Linear Regression/079 Residual Analysis (Part 1)_ Predicted vs Actual Values.mp4 153.6 MB
09 Introduction to Neural Networks and How to Use Pre-Trained Models/151 Costs and Disadvantages of Neural Networks.mp4 153.0 MB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/165 Fit a Keras Model and Use Tensorboard to Visualise Learning and Spot Problems.mp4 152.7 MB
12 Serving a Tensorflow Model through a Website/189 Loading a SavedModel.mp4 151.9 MB
05 Predict House Prices with Multivariable Linear Regression/074 Improving the Model by Transforming the Data.mp4 149.4 MB
02 Predict Movie Box Office Revenue with Linear Regression/010 Analyse and Evaluate the Results.mp4 149.1 MB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/163 Compiling a Keras Model and Understanding the Cross Entropy Loss Function.mp4 146.4 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/106 Tokenizing, Removing Stop Words and the Python Set Data Structure.mp4 144.8 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/125 Checkpoint_ Understanding the Data.mp4 140.9 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/103 Data Visualisation (Part 1)_ Pie Charts.mp4 137.4 MB
03 Python Programming for Data Science and Machine Learning/028 [Python] - Tips, Code Style and Naming Conventions.mp4 137.1 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/051 Running Gradient Descent with a MSE Cost Function.mp4 136.1 MB
09 Introduction to Neural Networks and How to Use Pre-Trained Models/152 Preprocessing Image Data and How RGB Works.mp4 135.9 MB
11 Use Tensorflow to Classify Handwritten Digits/179 TensorFlow Sessions and Batching Data.mp4 135.1 MB
12 Serving a Tensorflow Model through a Website/191 Introducing the Website Project and Tooling.mp4 131.5 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/118 Create the Vocabulary for the Spam Classifier.mp4 130.1 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/121 Sparse Matrix (Part 1)_ Split the Training and Testing Data.mp4 125.3 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/042 Implementing Batch Gradient Descent with SymPy.mp4 123.2 MB
05 Predict House Prices with Multivariable Linear Regression/082 Making Predictions (Part 2)_ Standard Deviation, RMSE, and Prediction Intervals.mp4 122.2 MB
07 Train a Naive Bayes Classifier to Create a Spam Filter_ Part 2/130 Count the Tokens to Train the Naive Bayes Model.mp4 116.8 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/123 Sparse Matrix (Part 3)_ Using groupby() and Saving .txt Files.mp4 116.2 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/035 Understanding the Power Rule & Creating Charts with Subplots.mp4 109.5 MB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/162 Pre-processing_ Scaling Inputs and Creating a Validation Dataset.mp4 108.7 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/047 Transposing and Reshaping Arrays.mp4 106.6 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/112 [Python] - Logical Operators to Create Subsets and Indices.mp4 106.2 MB
05 Predict House Prices with Multivariable Linear Regression/057 Clean and Explore the Data (Part 1)_ Understand the Nature of the Dataset.mp4 104.2 MB
07 Train a Naive Bayes Classifier to Create a Spam Filter_ Part 2/128 Setting up the Notebook and Understanding Delimiters in a Dataset.mp4 104.0 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/111 Advanced Subsetting on DataFrames_ the apply() Function.mp4 102.7 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/048 Implementing a MSE Cost Function.mp4 102.2 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/094 Bayes Theorem.mp4 99.1 MB
03 Python Programming for Data Science and Machine Learning/024 [Python] - Functions - Part 3_ Results & Return Values.mp4 98.9 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/116 Solving the Hamlet Challenge.mp4 97.1 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/113 Word Clouds & How to install Additional Python Packages.mp4 96.9 MB
05 Predict House Prices with Multivariable Linear Regression/056 Gathering the Boston House Price Data.mp4 95.5 MB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/138 Joint Conditional Probablity (Part 2)_ Priors.mp4 95.1 MB
05 Predict House Prices with Multivariable Linear Regression/075 How to Interpret Coefficients using p-Values and Statistical Significance.mp4 93.4 MB
11 Use Tensorflow to Classify Handwritten Digits/182 Name Scoping and Image Visualisation in Tensorboard.mp4 93.0 MB
11 Use Tensorflow to Classify Handwritten Digits/175 Data Preprocessing_ One-Hot Encoding and Creating the Validation Dataset.mp4 92.8 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/052 Visualising the Optimisation on a 3D Surface.mp4 92.5 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/045 Concatenating Numpy Arrays.mp4 89.3 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/101 Cleaning Data (Part 2)_ Working with a DataFrame Index.mp4 89.0 MB
11 Use Tensorflow to Classify Handwritten Digits/178 Defining the Cross Entropy Loss Function, the Optimizer and the Metrics.mp4 89.0 MB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/137 Joint Conditional Probability (Part 1)_ Dot Product.mp4 88.8 MB
03 Python Programming for Data Science and Machine Learning/018 [Python] - Variables and Types.mp4 88.4 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/107 Word Stemming & Removing Punctuation.mp4 87.7 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/049 Understanding Nested Loops and Plotting the MSE Function (Part 1).mp4 87.4 MB
05 Predict House Prices with Multivariable Linear Regression/070 How to Shuffle and Split Training & Testing Data.mp4 87.4 MB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/168 Model Evaluation and the Confusion Matrix.mp4 85.8 MB
03 Python Programming for Data Science and Machine Learning/015 Mac Users - Install Anaconda.mp4 85.3 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/102 Saving a JSON File with Pandas.mp4 85.2 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/034 LaTeX Markdown and Generating Data with Numpy.mp4 81.0 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/033 Introduction to Cost Functions.mp4 80.6 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/120 Coding Challenge_ Find the Longest Email.mp4 80.3 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/046 Introduction to the Mean Squared Error (MSE).mp4 78.8 MB
11 Use Tensorflow to Classify Handwritten Digits/173 Getting the Data and Loading it into Numpy Arrays.mp4 78.7 MB
05 Predict House Prices with Multivariable Linear Regression/071 Running a Multivariable Regression.mp4 77.6 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/104 Data Visualisation (Part 2)_ Donut Charts.mp4 77.0 MB
09 Introduction to Neural Networks and How to Use Pre-Trained Models/153 Importing Keras Models and the Tensorflow Graph.mp4 76.9 MB
05 Predict House Prices with Multivariable Linear Regression/062 Understanding Descriptive Statistics_ the Mean vs the Median.mp4 76.0 MB
05 Predict House Prices with Multivariable Linear Regression/059 Visualising Data (Part 1)_ Historams, Distributions & Outliers.mp4 75.4 MB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/142 False Positive vs False Negatives.mp4 75.1 MB
01 Introduction to the Course/002 What is Data Science_.mp4 75.1 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/095 Reading Files (Part 1)_ Absolute Paths and Relative Paths.mp4 74.6 MB
07 Train a Naive Bayes Classifier to Create a Spam Filter_ Part 2/132 Calculate the Token Probabilities and Save the Trained Model.mp4 74.0 MB
11 Use Tensorflow to Classify Handwritten Digits/176 What is a Tensor_.mp4 73.1 MB
02 Predict Movie Box Office Revenue with Linear Regression/007 Gather & Clean the Data.mp4 72.4 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/050 Plotting the Mean Squared Error (MSE) on a Surface (Part 2).mp4 72.2 MB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/139 Making Predictions_ Comparing Joint Probabilities.mp4 71.4 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/099 Create a Pandas DataFrame of Email Bodies.mp4 71.2 MB
03 Python Programming for Data Science and Machine Learning/016 Does LSD Make You Better at Maths_.mp4 70.2 MB
05 Predict House Prices with Multivariable Linear Regression/060 Visualising Data (Part 2)_ Seaborn and Probability Density Functions.mp4 69.4 MB
12 Serving a Tensorflow Model through a Website/187 What you'll make.mp4 67.5 MB
05 Predict House Prices with Multivariable Linear Regression/069 Understanding Multivariable Regression.mp4 64.6 MB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/144 The Precision Metric.mp4 64.5 MB
03 Python Programming for Data Science and Machine Learning/019 [Python] - Lists and Arrays.mp4 63.9 MB
09 Introduction to Neural Networks and How to Use Pre-Trained Models/149 The Human Brain and the Inspiration for Artificial Neural Networks.mp4 63.5 MB
12 Serving a Tensorflow Model through a Website/203 Publish and Share your Website!.mp4 62.4 MB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/159 Installing Tensorflow and Keras for Jupyter.mp4 61.3 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/105 Introduction to Natural Language Processing (NLP).mp4 61.0 MB
03 Python Programming for Data Science and Machine Learning/014 Windows Users - Install Anaconda.mp4 61.0 MB
05 Predict House Prices with Multivariable Linear Regression/055 Defining the Problem.mp4 60.6 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/088 How to Translate a Business Problem into a Machine Learning Problem.mp4 60.2 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/091 The Naive Bayes Algorithm and the Decision Boundary for a Classifier.mp4 59.9 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/097 Extracting the Text in the Email Body.mp4 57.9 MB
07 Train a Naive Bayes Classifier to Create a Spam Filter_ Part 2/133 Coding Challenge_ Prepare the Test Data.mp4 56.3 MB
03 Python Programming for Data Science and Machine Learning/022 [Python] - Functions - Part 1_ Defining and Calling Functions.mp4 49.3 MB
05 Predict House Prices with Multivariable Linear Regression/078 How to Analyse and Plot Regression Residuals.mp4 48.9 MB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/140 The Accuracy Metric.mp4 48.7 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/109 Creating a Function for Text Processing.mp4 46.9 MB
12 Serving a Tensorflow Model through a Website/197 Data Pre-Processing for Tensorflow.js.mp4 44.4 MB
12 Serving a Tensorflow Model through a Website/194 Adding a Favicon.mp4 44.2 MB
07 Train a Naive Bayes Classifier to Create a Spam Filter_ Part 2/131 Sum the Tokens across the Spam and Ham Subsets.mp4 41.6 MB
02 Predict Movie Box Office Revenue with Linear Regression/006 Introduction to Linear Regression & Specifying the Problem.mp4 40.7 MB
05 Predict House Prices with Multivariable Linear Regression/072 How to Calculate the Model Fit with R-Squared.mp4 40.4 MB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/158 Solving a Business Problem with Image Classification.mp4 39.4 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/124 Coding Challenge Solution_ Preparing the Test Data.mp4 39.4 MB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/136 Set up the Testing Notebook.mp4 38.7 MB
11 Use Tensorflow to Classify Handwritten Digits/174 Data Exploration and Understanding the Structure of the Input Data.mp4 37.4 MB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/160 Gathering the CIFAR 10 Dataset.mp4 37.1 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/090 How to Add the Lesson Resources to the Project.mp4 36.8 MB
01 Introduction to the Course/001 What is Machine Learning_.mp4 33.9 MB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/143 The Recall Metric.mp4 33.5 MB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/145 The F-score or F1 Metric.mp4 30.1 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/031 What's Coming Up_.mp4 25.8 MB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/136 SpamData.zip 23.9 MB
07 Train a Naive Bayes Classifier to Create a Spam Filter_ Part 2/128 SpamData.zip 23.4 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/089 SpamData.zip 22.3 MB
05 Predict House Prices with Multivariable Linear Regression/063 Introduction to Correlation_ Understanding Strength & Direction.mp4 21.4 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/119 Coding Challenge_ Check for Membership in a Collection.mp4 20.9 MB
02 Predict Movie Box Office Revenue with Linear Regression/009 The Intuition behind the Linear Regression Model.mp4 20.4 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/032 How a Machine Learns.mp4 17.4 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/092 Basic Probability.mp4 16.3 MB
11 Use Tensorflow to Classify Handwritten Digits/173 MNIST.zip 15.5 MB
05 Predict House Prices with Multivariable Linear Regression/073 Introduction to Model Evaluation.mp4 12.6 MB
11 Use Tensorflow to Classify Handwritten Digits/172 What's coming up_.mp4 8.0 MB
12 Serving a Tensorflow Model through a Website/202 math-garden-stub-complete.zip 4.3 MB
12 Serving a Tensorflow Model through a Website/198 math-garden-stub-12.12-checkpoint.zip 4.3 MB
05 Predict House Prices with Multivariable Linear Regression/086 04-Multivariable-Regression.ipynb.zip 3.7 MB
12 Serving a Tensorflow Model through a Website/189 MNIST-Model-Load-Files.zip 3.0 MB
03 Python Programming for Data Science and Machine Learning/017 12-Rules-to-Learn-to-Code.pdf 2.4 MB
12 Serving a Tensorflow Model through a Website/190 TFJS.zip 1.6 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/053 03-Gradient-Descent.ipynb.zip 1.2 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/126 06-Bayes-Classifier-Pre-Processing.ipynb.zip 1.0 MB
09 Introduction to Neural Networks and How to Use Pre-Trained Models/156 09-Neural-Nets-Pretrained-Image-Classification.ipynb.zip 585.6 kB
09 Introduction to Neural Networks and How to Use Pre-Trained Models/152 TF-Keras-Classification-Images.zip 513.1 kB
02 Predict Movie Box Office Revenue with Linear Regression/007 cost-revenue-dirty.csv 383.7 kB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/147 07-Bayes-Classifier-Testing-Inference-Evaluation.ipynb.zip 248.9 kB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/170 10-Neural-Nets-Keras-CIFAR10-Classification.ipynb.zip 123.0 kB
01 Introduction to the Course/003 ML-Data-Science-Syllabus.pdf 106.5 kB
02 Predict Movie Box Office Revenue with Linear Regression/008 cost-revenue-clean.csv 93.0 kB
02 Predict Movie Box Office Revenue with Linear Regression/011 01-Linear-Regression-complete.ipynb.zip 77.1 kB
12 Serving a Tensorflow Model through a Website/191 math-garden-stub.zip 45.1 kB
04 Introduction to Optimisation and the Gradient Descent Algorithm/036 [Python] - Loops and the Gradient Descent Algorithm.en_US.srt 41.2 kB
04 Introduction to Optimisation and the Gradient Descent Algorithm/037 [Python] - Advanced Functions and the Pitfalls of Optimisation (Part 1).en_US.srt 40.5 kB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/169 Model Evaluation and the Confusion Matrix.en_US.srt 39.9 kB
12 Serving a Tensorflow Model through a Website/195 Styling an HTML Canvas.en_US.srt 38.9 kB
02 Predict Movie Box Office Revenue with Linear Regression/009 01-Linear-Regression-checkpoint.ipynb.zip 38.5 kB
12 Serving a Tensorflow Model through a Website/198 Introduction to OpenCV.en_US.srt 37.8 kB
12 Serving a Tensorflow Model through a Website/202 Adding the Game Logic.en_US.srt 37.4 kB
12 Serving a Tensorflow Model through a Website/192 HTML and CSS Styling.en_US.srt 37.4 kB
03 Python Programming for Data Science and Machine Learning/029 02-Python-Intro.ipynb.zip 37.3 kB
12 Serving a Tensorflow Model through a Website/196 Drawing on an HTML Canvas.en_US.srt 37.2 kB
12 Serving a Tensorflow Model through a Website/193 Loading a Tensorflow.js Model and Starting your own Server.en_US.srt 36.7 kB
04 Introduction to Optimisation and the Gradient Descent Algorithm/039 Understanding the Learning Rate.en_US.srt 35.5 kB
12 Serving a Tensorflow Model through a Website/200 Calculating the Centre of Mass and Shifting the Image.en_US.srt 34.9 kB
03 Python Programming for Data Science and Machine Learning/021 [Python] - Module Imports.en_US.srt 34.2 kB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/146 A Naive Bayes Implementation using SciKit Learn.en_US.srt 33.1 kB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/141 Visualising the Decision Boundary.en_US.srt 33.0 kB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/167 Use the Model to Make Predictions.en_US.srt 32.5 kB
04 Introduction to Optimisation and the Gradient Descent Algorithm/038 [Python] - Tuples and the Pitfalls of Optimisation (Part 2).en_US.srt 31.6 kB
11 Use Tensorflow to Classify Handwritten Digits/183 Different Model Architectures_ Experimenting with Dropout.en_US.srt 29.7 kB
02 Predict Movie Box Office Revenue with Linear Regression/008 Explore & Visualise the Data with Python.en_US.srt 29.3 kB
11 Use Tensorflow to Classify Handwritten Digits/177 Creating Tensors and Setting up the Neural Network Architecture.en_US.srt 28.6 kB
03 Python Programming for Data Science and Machine Learning/025 [Python] - Objects - Understanding Attributes and Methods.en_US.srt 28.2 kB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/166 Use Regularisation to Prevent Overfitting_ Early Stopping & Dropout Techniques.en_US.srt 27.9 kB
09 Introduction to Neural Networks and How to Use Pre-Trained Models/150 Layers, Feature Generation and Learning.en_US.srt 27.4 kB
05 Predict House Prices with Multivariable Linear Regression/068 Working with Seaborn Pairplots & Jupyter Microbenchmarking Techniques.en_US.srt 27.2 kB
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03 Python Programming for Data Science and Machine Learning/020 [Python & Pandas] - Dataframes and Series.en_US.srt 26.6 kB
12 Serving a Tensorflow Model through a Website/199 Resizing and Adding Padding to Images.en_US.srt 26.4 kB
11 Use Tensorflow to Classify Handwritten Digits/182 Name Scoping and Image Visualisation in Tensorboard.en_US.srt 25.9 kB
12 Serving a Tensorflow Model through a Website/189 Loading a SavedModel.en_US.srt 25.8 kB
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03 Python Programming for Data Science and Machine Learning/026 How to Make Sense of Python Documentation for Data Visualisation.en_US.srt 25.1 kB
04 Introduction to Optimisation and the Gradient Descent Algorithm/040 How to Create 3-Dimensional Charts.en_US.srt 24.6 kB
05 Predict House Prices with Multivariable Linear Regression/076 Understanding VIF & Testing for Multicollinearity.en_US.srt 24.2 kB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/164 Interacting with the Operating System and the Python Try-Catch Block.en_US.srt 23.4 kB
05 Predict House Prices with Multivariable Linear Regression/065 Visualising Correlations with a Heatmap.en_US.srt 23.1 kB
11 Use Tensorflow to Classify Handwritten Digits/180 Tensorboard Summaries and the Filewriter.en_US.srt 22.9 kB
05 Predict House Prices with Multivariable Linear Regression/081 Making Predictions (Part 1)_ MSE & R-Squared.en_US.srt 22.4 kB
05 Predict House Prices with Multivariable Linear Regression/077 Model Simplification & Baysian Information Criterion.en_US.srt 21.9 kB
04 Introduction to Optimisation and the Gradient Descent Algorithm/044 Reshaping and Slicing N-Dimensional Arrays.en_US.srt 21.7 kB
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07 Train a Naive Bayes Classifier to Create a Spam Filter_ Part 2/129 Create a Full Matrix.en_US.srt 21.4 kB
02 Predict Movie Box Office Revenue with Linear Regression/010 Analyse and Evaluate the Results.en_US.srt 21.3 kB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/098 [Python] - Generator Functions & the yield Keyword.en_US.srt 21.2 kB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/122 Sparse Matrix (Part 2)_ Data Munging with Nested Loops.en_US.srt 21.1 kB
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11 Use Tensorflow to Classify Handwritten Digits/181 Understanding the Tensorflow Graph_ Nodes and Edges.en_US.srt 20.9 kB
12 Serving a Tensorflow Model through a Website/190 Converting a Model to Tensorflow.js.en_US.srt 20.8 kB
05 Predict House Prices with Multivariable Linear Regression/074 Improving the Model by Transforming the Data.en_US.srt 20.4 kB
11 Use Tensorflow to Classify Handwritten Digits/179 TensorFlow Sessions and Batching Data.en_US.srt 20.2 kB
05 Predict House Prices with Multivariable Linear Regression/084 [Python] - Conditional Statements - Build a Valuation Tool (Part 2).en_US.srt 20.1 kB
03 Python Programming for Data Science and Machine Learning/023 [Python] - Functions - Part 2_ Arguments & Parameters.en_US.srt 19.7 kB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/162 Pre-processing_ Scaling Inputs and Creating a Validation Dataset.en_US.srt 19.6 kB
05 Predict House Prices with Multivariable Linear Regression/061 Working with Index Data, Pandas Series, and Dummy Variables.en_US.srt 19.6 kB
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05 Predict House Prices with Multivariable Linear Regression/066 Techniques to Style Scatter Plots.en_US.srt 19.5 kB
04 Introduction to Optimisation and the Gradient Descent Algorithm/041 Understanding Partial Derivatives and How to use SymPy.en_US.srt 19.2 kB
09 Introduction to Neural Networks and How to Use Pre-Trained Models/151 Costs and Disadvantages of Neural Networks.en_US.srt 19.0 kB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/093 Joint & Conditional Probability.en_US.srt 18.8 kB
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09 Introduction to Neural Networks and How to Use Pre-Trained Models/154 Making Predictions using InceptionResNet.en_US.srt 18.6 kB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/163 Compiling a Keras Model and Understanding the Cross Entropy Loss Function.en_US.srt 18.4 kB
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05 Predict House Prices with Multivariable Linear Regression/079 Residual Analysis (Part 1)_ Predicted vs Actual Values.en_US.srt 17.2 kB
04 Introduction to Optimisation and the Gradient Descent Algorithm/043 [Python] - Loops and Performance Considerations.en_US.srt 17.1 kB
04 Introduction to Optimisation and the Gradient Descent Algorithm/035 Understanding the Power Rule & Creating Charts with Subplots.en_US.srt 17.0 kB
12 Serving a Tensorflow Model through a Website/191 Introducing the Website Project and Tooling.en_US.srt 17.0 kB
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09 Introduction to Neural Networks and How to Use Pre-Trained Models/152 Preprocessing Image Data and How RGB Works.en_US.srt 15.9 kB
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03 Python Programming for Data Science and Machine Learning/024 [Python] - Functions - Part 3_ Results & Return Values.en_US.srt 15.7 kB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/103 Data Visualisation (Part 1)_ Pie Charts.en_US.srt 15.3 kB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/112 [Python] - Logical Operators to Create Subsets and Indices.en_US.srt 15.2 kB
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06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/094 Bayes Theorem.en_US.srt 14.4 kB
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11 Use Tensorflow to Classify Handwritten Digits/178 Defining the Cross Entropy Loss Function, the Optimizer and the Metrics.en_US.srt 13.9 kB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/165 Fit a Keras Model and Use Tensorboard to Visualise Learning and Spot Problems.en_US.srt 13.9 kB
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02 Predict Movie Box Office Revenue with Linear Regression/007 Gather & Clean the Data.en_US.srt 13.2 kB
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06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/111 Advanced Subsetting on DataFrames_ the apply() Function.en_US.srt 12.8 kB
04 Introduction to Optimisation and the Gradient Descent Algorithm/048 Implementing a MSE Cost Function.en_US.srt 12.8 kB
09 Introduction to Neural Networks and How to Use Pre-Trained Models/155 Coding Challenge Solution_ Using other Keras Models.en_US.srt 12.8 kB
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08 Test and Evaluate a Naive Bayes Classifier_ Part 3/142 False Positive vs False Negatives.en_US.srt 12.6 kB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/137 Joint Conditional Probability (Part 1)_ Dot Product.en_US.srt 12.5 kB
11 Use Tensorflow to Classify Handwritten Digits/175 Data Preprocessing_ One-Hot Encoding and Creating the Validation Dataset.en_US.srt 12.5 kB
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04 Introduction to Optimisation and the Gradient Descent Algorithm/046 Introduction to the Mean Squared Error (MSE).en_US.srt 12.0 kB
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05 Predict House Prices with Multivariable Linear Regression/062 Understanding Descriptive Statistics_ the Mean vs the Median.en_US.srt 11.6 kB
03 Python Programming for Data Science and Machine Learning/019 [Python] - Lists and Arrays.en_US.srt 11.5 kB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/123 Sparse Matrix (Part 3)_ Using groupby() and Saving .txt Files.en_US.srt 11.5 kB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/113 Word Clouds & How to install Additional Python Packages.en_US.srt 11.4 kB
09 Introduction to Neural Networks and How to Use Pre-Trained Models/153 Importing Keras Models and the Tensorflow Graph.en_US.srt 11.3 kB
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09 Introduction to Neural Networks and How to Use Pre-Trained Models/149 The Human Brain and the Inspiration for Artificial Neural Networks.en_US.srt 10.7 kB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/168 Model Evaluation and the Confusion Matrix.en_US.srt 10.6 kB
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02 Predict Movie Box Office Revenue with Linear Regression/009 The Intuition behind the Linear Regression Model.en_US.srt 10.3 kB
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04 Introduction to Optimisation and the Gradient Descent Algorithm/052 Visualising the Optimisation on a 3D Surface.en_US.srt 10.2 kB
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04 Introduction to Optimisation and the Gradient Descent Algorithm/033 Introduction to Cost Functions.en_US.srt 9.0 kB
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04 Introduction to Optimisation and the Gradient Descent Algorithm/045 Concatenating Numpy Arrays.en_US.srt 8.5 kB
03 Python Programming for Data Science and Machine Learning/014 Windows Users - Install Anaconda.en_US.srt 8.4 kB
02 Predict Movie Box Office Revenue with Linear Regression/006 Introduction to Linear Regression & Specifying the Problem.en_US.srt 8.3 kB
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05 Predict House Prices with Multivariable Linear Regression/063 Introduction to Correlation_ Understanding Strength & Direction.en_US.srt 8.0 kB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/105 Introduction to Natural Language Processing (NLP).en_US.srt 7.8 kB
03 Python Programming for Data Science and Machine Learning/015 Mac Users - Install Anaconda.en_US.srt 7.7 kB
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03 Python Programming for Data Science and Machine Learning/016 Does LSD Make You Better at Maths_.en_US.srt 7.0 kB
04 Introduction to Optimisation and the Gradient Descent Algorithm/032 How a Machine Learns.en_US.srt 6.9 kB
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01 Introduction to the Course/001 What is Machine Learning_.en_US.srt 6.6 kB
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01 Introduction to the Course/002 What is Data Science_.en_US.srt 5.5 kB
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06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/092 Basic Probability.en_US.srt 5.0 kB
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03 Python Programming for Data Science and Machine Learning/025 [exercise_solution] Python Functions Coding Exercise - Part 3.zip 190 Bytes
03 Python Programming for Data Science and Machine Learning/019 [exercise_solution] Python Variable Coding Exercise.zip 173 Bytes
05 Predict House Prices with Multivariable Linear Regression/085 [exercise] Python Conditional Statement Coding Exercise.zip 167 Bytes
03 Python Programming for Data Science and Machine Learning/020 lsd-math-score-data.csv 155 Bytes
01 Introduction to the Course/004 App-Brewery-Cornell-Notes-Template.txt 81 Bytes
02 Predict Movie Box Office Revenue with Linear Regression/006 Course-Resources.txt 62 Bytes
03 Python Programming for Data Science and Machine Learning/014 Course-Resources.txt 62 Bytes
03 Python Programming for Data Science and Machine Learning/015 Course-Resources.txt 62 Bytes
04 Introduction to Optimisation and the Gradient Descent Algorithm/031 Course-Resources.txt 62 Bytes
05 Predict House Prices with Multivariable Linear Regression/055 Course-Resources.txt 62 Bytes
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/088 Course-Resources.txt 62 Bytes
07 Train a Naive Bayes Classifier to Create a Spam Filter_ Part 2/128 Course-Resources.txt 62 Bytes
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/136 Course-Resources.txt 62 Bytes
09 Introduction to Neural Networks and How to Use Pre-Trained Models/149 Course-Resources.txt 62 Bytes
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/158 Course-Resources.txt 62 Bytes
11 Use Tensorflow to Classify Handwritten Digits/172 Course-Resources.txt 62 Bytes
02 Predict Movie Box Office Revenue with Linear Regression/007 The-Numbers-Movie-Budgets.txt 42 Bytes
02 Predict Movie Box Office Revenue with Linear Regression/008 Try-Jupyter-in-your-Browser.txt 25 Bytes

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