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Machine Learning and Deep Learning with Python - SBRCMLDL001
First Section
Introduction to Machine Learning (157:09)
Python Fundamentals
Intoduction-to-Jupyter Console (17:35)
DataStructures List (73:06)
DataStructures Tuple (29:56)
Working with Strings (9:09)
Dictionaries (30:38)
Sets (22:36)
Exploratory Data Analysis
Exploratory Data Analysis -Part1 (54:54)
Exploratory data Analysis - Partt2 (43:53)
Exploratory Data Analysis - Part 3 (85:08)
Exploratory Data Analysis- part4 (107:41)
Exploratory data Analysis - part 5 (49:49)
Data-PreProcessing
Data Preprocessing 1 (16:28)
Outlier Analysis (78:51)
Handling Null Values (117:33)
Machine Learning - Supervised Algorithms
Intro to Supervised Learning - Regression 1 (125:55)
Linear Regression part 2 (67:56)
Linear Reg 2 (129:35)
Polynomial Regression (71:20)
Decision Tree Regressor (81:23)
Random Forest Regressor (57:53)
Classification Introduction (50:46)
Classification (31:11)
KNN - introduction (79:58)
KNN implementation (34:55)
Logistic Regression (65:50)
Naive Bias (28:49)
SVM (37:55)
Decision Tree -classification part1 (7:56)
Model Performance Evaluation (67:20)
Decision Tree Random Forest and Comparision of different classification algorithms (108:15)
Machine Learning - UnSupervised Algorithms
Clustering Introduction (56:51)
Cluster Analysis (108:11)
Implenetation of K Means (55:57)
Model Deployments
Deploying ML Model using Flask (135:18)
Flask Application Deployement on IBM Cloud (140:42)
Artificial Neural Networks
Introduction to ANN (169:35)
ANN Implementation (81:04)
CNN Introduction (94:31)
CNN Implementation (176:48)
NLP Part 1 (111:06)
NLP Part 2 (55:46)
RNN Implementation (72:56)
RNN Continuation (111:42)
Introduction to Artificial Neural Network (20:39)
How ANN Learn (68:43)
Activation function functions & Weights (32:01)
ANN Practical Implementation (44:57)
Decision Tree Random Forest and Comparision of different classification algorithms
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