Section 1 : Introduction
Section 2 : Setup (Google Colab) & Download Code
Section 3 : Introduction to Python
Section 4 : Pandas
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Lecture 19
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Pandas Introduction
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2:48
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Lecture 20
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Pandas 1 - Data Series
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6:17
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Lecture 21
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Pandas 2A - DataFrames - Index, Slice, Stats, Finding Empty cells
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17:31
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Lecture 22
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Pandas 2B - DataFrames - Index, Slice, Stats, Finding Empty cells & Filtering
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5:51
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Lecture 23
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Pandas 3A - Data Cleaning - Alter ColomnsRows, Missing Data & String Operations
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8:46
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Lecture 24
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Pandas 3B - Data Cleaning - Alter ColomnsRows, Missing Data & String Operations
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19:46
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Lecture 25
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INTRODUCTION TO BRAINMEASURES PROCTOR SYSTEM
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Pdf
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Lecture 26
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Pandas 5 - Feature Engineer, Lambda and Apply
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4:24
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Lecture 27
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Pandas 6 - Concatenating, Merging and Joinining
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15:21
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Lecture 28
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Pandas 7 - Time Series Data
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9:56
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Lecture 29
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Pandas 8 - ADVANCED Operations - Iterows, Vectorization and Numpy
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11:17
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Lecture 30
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Pandas 9 - ADVANCED Operations - Iterows, Vectorization and Numpy
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4:29
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Lecture 31
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Pandas 10 - ADVANCED Operations - Parallel Processing
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4:24
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Lecture 32
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Map Visualizations with Plotly - Cloropeths from Scratch - USA and World
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11:25
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Lecture 33
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Map Visualizations with Plotly - Heatmaps, Scatter Plots and Lines
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4:55
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Section 5 : Statistics & Visualizations
Section 6 : Probability Theory
Section 7 : Hypothesis Testing
Section 8 : AB Testing - A Worked Example
Section 9 : Data Dashboards - Google Data Studio
Section 10 : Machine Learning
Section 11 : Deep Learning
Section 12 : Unsupervised Learning - Clustering
Section 13 : Dimensionality Reduction
Section 14 : Recommendation Systems
Section 15 : Natural Language Processing
Section 16 : Big Data
Section 17 : Predicting the US 2020 Election
Section 18 : Predicting Diabetes Cases
Section 19 : Market Basket Analysis
Section 20 : Predicting the World Cup Winner (SoccerFootball)
Section 21 : Covid-19 Data Analysis and Flourish Bar Chart Race Visualization
Section 22 : Analyzing Olmypic Winners
Section 23 : Is Home Advantage Real in Soccer and Basketball
Section 24 : IPL Cricket Data Analysis
Section 25 : Streaming Services (Netflix, Hulu, Disney Plus and Amazon Prime) - Movie Analysi
Section 26 : Micro Brewery and Pub Data Analysis
Section 27 : Pizza Resturant Data Analysis
Section 28 : Supply Chain Data Analysis
Section 29 : Indian Election Result Analysis
Section 30 : Africa Economic Crisis Data Analysis
Section 31 : Predicting Which Employees May Quit
Section 32 : Figuring Out Which Customers May Leave
Section 33 : Who to Target For Donations
Section 34 : Predicting Insurance Premiums
Section 35 : Predicting Airbnb Prices
Section 36 : Detecting Credit Card Fraud
Section 37 : Analyzing Conversion Rates in Marketing Campaigns
Section 38 : Predicting Advertising Engagement
Section 39 : Product Sales Analysis
Section 40 : Determing Your Most Valuable Customers
Section 41 : Customer Clustering (K-means, Hierarchial) - Train Passenger
Section 42 : Build a Product Recommendation System
Section 43 : Movie Recommendation System - LiteFM
Section 44 : Deep Learning Recommendation System
Section 45 : Predicting Brent Oil Prices
Section 46 : Stock Trading using Reinforcement Learning
Section 47 : SalesDemand Forecasting
Section 48 : Detecting Sentiment in Tweets
Section 49 : Spam or Ham Detection
Section 50 : Explore Data with PySpark and Titanic Surival Prediction
Section 51 : Newspaper Headline Classification using PySpark
Section 52 : Deployment into Production