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Data Science Full Course - 12 Hours | Data Science For Beginners [2023] | Edureka(55)
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Introduction (
00:00:00
)
Agenda (
00:00:45
)
What is Data Science (
00:02:59
)
Data Science Basics (
00:04:31
)
Walmart use cases (
00:07:13
)
Who is a Data Scientist (
00:12:05
)
Role of a Data Scientist (
00:13:47
)
Technologies to learn for a Data scientist (
00:15:39
)
Data Scientist Roadmap (
00:44:16
)
Data Science Salary (
01:00:55
)
Statistics and Probability (
01:09:44
)
Use Case (
01:40:48
)
Confusion matrix (
01:50:43
)
Probability (
02:00:15
)
Bayes Theorem (
02:15:56
)
Inferntial Statistics (
02:22:22
)
Use Case (
02:31:37
)
What is Machine Learning (
02:42:20
)
What is Regression in Machine Learning (
02:59:23
)
Use Case (
03:08:05
)
Logistic Regression (
03:25:53
)
Use case (
03:32:46
)
Decision Tree Algorithm (
04:14:25
)
What is Classification (
04:15:01
)
Types of Classification (
04:19:12
)
What is Decision Tree (
04:28:28
)
Decesion Tree Terminologies (
04:35:35
)
Random Forest (
04:59:50
)
Working of Random Forest (
05:03:11
)
RandomSampling with Replacement (
05:04:08
)
Advantages of Random Forest (
05:12:15
)
Hands-on Random forest (
05:15:37
)
KNN Algorithm (
05:27:01
)
Features of KNN (
05:29:02
)
How Does KNN Algorithm Works (
05:37:17
)
Hands-on KNN Algorithm (
05:42:50
)
Naive Bayes Classifier (
05:59:30
)
Support Vector Machine (
06:19:50
)
K-means clustering Algorithm (
06:45:16
)
Apriori Algorithm (
07:05:27
)
Hands-on (
07:21:14
)
Reinforcement Learning (
07:35:08
)
Reinforcement Learning - Counter strike example (
07:38:25
)
Q Learning (
07:56:36
)
Defining a problem statement (
07:57:34
)
The Bellman Equation (
08:01:37
)
What is Deep Learning (
08:19:25
)
Why do we need Artificial Neuron (
08:23:24
)
WHat is Tensorflow (
08:33:55
)
Tensorflow Code Basics (
08:43:50
)
What is Computational Graph (
08:55:45
)
Limitation of a Single layer perception (
09:18:18
)
Multi-layer Perceptron Use case (
09:25:54
)
Data Scientist Resume (
09:57:08
)
Data Science Interview Question & Answers (
10:02:33
)
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