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VIT-B-Artificial Intelligence
First Section
Introduction_to_Artificial_intelligence (119:11)
Anaconda_installation_and_Smartinternz_platform_Demo (44:33)
Introuction_to_Python (22:17)
IBM_Academic_initiative-Part_1 (16:23)
IBM_Academic_initiative-Part_2 (4:59)
Variables_and_Data_types-1 (116:58)
Data_types_loops_and_statements (113:10)
Functions_Exception_and_File_Handlings (109:13)
Python_for_Datascience_-Numpy (101:38)
Pandas_ (121:27)
Matplotlib_and_Seaborn (122:27)
Data_preprocessing (116:16)
Simple_Linear_Regression (97:10)
Simple_linear_regression_practical_ (108:47)
Artificial_Neural_Networks (104:25)
Stochastic_Gradient_Descent_and_Neural_Network_process_ (105:02)
ANN_practical_ (96:39)
CNN_theory (99:52)
CNN_practical (91:08)
RNN_theory (93:35)
RNN_practical (105:30)
RNN_practical-2 (97:10)
NLP (126:35)
Flask (80:14)
IBM_AutoAI_Experiment (80:49)
Node-RED (65:39)
Stochastic_Gradient_Descent_and_Neural_Network_process_
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