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Data Science Foundations - Excel with Python and NumPy for Powerful Insights
Numpy
00 Course Intro (5:11)
01 Intro to Numpy (6:20)
02 Installing Numpy (3:59)
03 Creating Numpy Arrays (16:55)
04 Creating Numpy Matrices (11:57)
05 Getting and Setting Numpy Elements (16:59)
06 Arithmetic Operations on Numpy Arrays (11:56)
07 Numpy Functions Part 1 (19:13)
08 Numpy Functions Part 2 (12:36)
09 Summary and Outro (3:01)
Numpy_Code
Numpy Slides
Learning about Pandas
00 Panda Course Introduction (5:43)
01 Intro to Pandas (7:55)
02 Installing Pandas (5:28)
03 Creating Pandas Series (20:34)
04 Date Ranges (11:29)
05 Getting Elements from Series (19:21)
06 Getting Properties of Series (13:04)
07 Modifying Series (19:02)
08 Operations on Series (11:48)
09 Creating Pandas DataFrames (22:57)
10 Getting Elements from DataFrames (25:12)
11 Getting Properties from DataFrames (17:44)
12 Dataframe Modification (36:24)
13 DataFrame Operations (20:09)
14 DataFrame Comparisons and Iteration (15:35)
15 Reading CSVs (12:00)
16 Summary and Outro (4:14)
17 PandasPracticeCSV
Pandas_Code
Pandas Slides
Learning about PyPlot
00 Course Intro (5:30)
01 Intro to Pyplot (5:11)
02 Installing Matplotlib (5:51)
03 Basic Line Plot (7:53)
04 Customizing Graphs (10:47)
05 Plotting Multiple Datasets (8:10)
06 Bar Chart (6:26)
07 Pie Chart (9:13)
08 Histogram (10:14)
09 3D Plotting (6:28)
10 Course Outro (4:09)
Pyplot Code
Machine Learning Theory
00 Course Intro (6:05)
01 Quick Intro to Machine Learning (18:02)
02 Deep Dive into Machine Learning (12:02)
03 Problems Solved with Machine Learning Part 1 (13:26)
04 Problems Solved with Machine Learning Part 2 (16:25)
05 Types of Machine Learning (10:15)
06 How Machine Learning Works (23:20)
07 Common Machine Learning Structures (13:51)
08 Steps to Build a Machine Learning Program (16:34)
09 Summary and Outro (2:49)
Intro to Machine Learning Slides
Intro to Tensorflow
00 Course Intro (6:10)
01 Intro to Tensorflow (11:06)
02 Installing Tensorflow (7:44)
03 Intro to Linear Regression (9:26)
04 Linear Regression Model - Creating Dataset (5:49)
05 Linear Regression Model - Building the Model (7:22)
06 Linear Regression Model - Creating a Loss Function (5:57)
07 Linear Regression Model - Training the Model (12:42)
08 Linear Regression Model - Testing the Model (5:22)
09 Summary and Outro (2:55)
Intro to Tensorflow Slides
Linear_Regression Code
Review Sentiment Analysis
00 Course Intro (6:19)
01 How Machines Interpret Text (15:23)
02 Building the Model Part 1 - Examining Dataset (12:27)
03 Building the Model Part 2 - Formatting Dataset (15:14)
04 Building the Model Part 3 - Building the Model (10:30)
05 Building the Model Part 4 - Training the Model (11:24)
06 Building the Model Part 5 - Testing the Model (9:26)
07 Course Summary and Outro (3:29)
Review Sentiment Analysis code
Review Predictor Slides
08 Steps to Build a Machine Learning Program
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