User:Shrikarsan/sandbox

2:44 Introduction to Data Science 9:55 Data Analysis at Walmart 13:20 What is Data Science? 14:39 Who is a Data Scientist? 16:50 Data Science Skill Set 21:51 Data Science Job Roles 26:58 Data Life Cycle 30:25 Statistics & Probability 34:31 Categories of Data 34:50 Qualitative Data 36:09 Quantitative Data 39:11 What is Statistics? 41:32 Basic Terminologies in Statistics 42:50 Sampling Techniques 45:31 Random Sampling 46:20 Systematic Sampling 46:50 Stratified Sampling 47:54 Types of Statistics 50:38 Descriptive Statistics 55:52 Measures of Spread 55:56 Range 56:44 Inter Quartile Range 58:58 Variance 59:36 Standard Deviation 1:14:25 Confusion Matrix 1:19:16 Probability 1:24:14 What is Probability? 1:27:13 Types of Events 1:27:58 Probability Distribution 1:28:15 Probability Density Function 1:30:02 Normal Distribution 1:30:51 Standard Deviation & Curve 1:31:19 Central Limit Theorem 1:33:12 Types of Probablity 1:33:34 Marginal Probablity 1:34:06 Joint Probablity 1:34:58 Conditional Probablity 1:35:56 Use-Case 1:39:46 Bayes Theorem 1:45:44 Inferential Statistics 1:56:40 Hypothesis Testing 2:00:34 Basics of Machine Learning 2:01:41 Need for Machine Learning 2:07:03 What is Machine Learning? 2:09:21 Machine Learning Definitions 2:!1:48 Machine Learning Process 2:18:31 Supervised Learning Algorithm 2:19:54 What is Regression? 2:21:23 Linear vs Logistic Regression 2:33:51 Linear Regression 2:25:27 Where is Linear Regression used? 2:27:11 Understanding Linear Regression 2:37:00 What is R-Square? 2:46:35 Logistic Regression 2:51:22 Logistic Regression Curve 2:53:02 Logistic Regression Equation 2:56:21 Logistic Regression Use-Cases 2:58:23 Demo 3:00:57 Implement Logistic Regression 3:02:33 Import Libraries 3:05:28 Analyzing Data 3:11:52 Data Wrangling 3:23:54 Train & Test Data 3:20:44 Implement Logistic Regression 3:31:04 SUV Data Analysis 3:38:44 Decision Trees 3:39:50 What is Classification? 3:42:27 Types of Classification 3:42:27 Decision Tree 3:43:51 Random Forest 3:45:06 Naive Bayes 3:47:12 KNN 3:49:02 What is Decision Tree? 3:55:15 Decision Tree Terminologies 3:56:51 CART Algorithm 3:58:50 Entropy 4:00:15 What is Entropy? 4:23:52 Random Forest 4:27:29 Types of Classifier 4:31:17 Why Random Forest? 4:39:14 What is Random Forest? 4:51:26 How Random Forest Works? 4:51:36 Random Forest Algorithm 5:04:23 K Nearest Neighbour 5:05:33 What is KNN Algorithm? 5:08:50 KNN Algorithm Working 5:14:55 kNN Example 5:24:30 What is Naive Bayes? 5:25:13 Bayes Theorem 5:27:48 Bayes Theorem Proof 5:29:43 Naive Bayes Working 5:39:06 Types of Naive Bayes 5:53:37 Support Vector Machine 5:57:40 What is SVM? 5:59:46 How does SVM work? 6:03:00 Introduction to Non-Linear SVM 6:04:48 SVM Example 6:06:12 Unsupervised Learning Algorithms - KMeans 6:06:18 What is Unsupervised Learning? 6:06:45 Unsupervised Learning: Process Flow 6:07:17 What is Clustering? 6:09:15 Types of Clustering 6:10:15 K-Means Clustering 6:10:40 K-Means Algorithm Working 6:16:17 K-Means Algorithm 6:19:16 Fuzzy C-Means Clustering 6:21:22 Hierarchical Clustering 6:22:53 Association Clustering 6:24:57 Association Rule Mining 6:30:35 Apriori Algorithm 6:37:45 Apriori Demo 6:40:49 What is Reinforcement Learning? 6:42:48 Reinforcement Learning Process 6:51:10 Markov Decision Process 6:54:53 Understanding Q - Learning 7:13:12 Q-Learning Demo 7:25:34 The Bellman Equation 7:48:39 What is Deep Learning? 7:52:53 Why we need Artificial Neuron? 7:54:33 Perceptron Learning Algorithm 7:57:57 Activation Function 8:03:14 Single Layer Perceptron 8:04:04 What is Tensorflow? 8:07:25 Demo 8:21:03 What is a Computational Graph? 8:49:18 Limitations of Single Layer Perceptron 8:50:08 Multi-Layer Perceptron 8:51:24 What is Backpropagation? 8:52:26 Backpropagation Learning Algorithm 8:59:31 Multi-layer Perceptron Demo 9:01:23 Data Science Interview Questions

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