Python ML,DL & AI Dec Batch
19 STUDENTS ENROLLED
Course Curriculum
| Session 1 Python Programming Intro | |||
| PYTHON ML SESSION 1 VIDEO 1 PYTHON PROGRAMMING INTRO Details | 00:00:00 | ||
| Session 2 Intermediate Python Programming and Functions | |||
| PYTHON ML SESSION 2 Part-1 Functions 23-12-2020 Details | 00:00:00 | ||
| PYTHON ML SESSION 2 Part-2 Lambda Functions Map and Filter 23-12-2020 Details | 00:00:00 | ||
| PYTHON ML SESSION 2 Part-3 Packages and Classes 23-12-2020 Details | 00:00:00 | ||
| Session 3 Data Manipulation With Pandas | |||
| Session 3 Data Manipulation with Pandas Details | 00:00:00 | ||
| Session 4 Basic Statistics | |||
| Video1_Mean Details | 00:00:00 | ||
| Video2_Google_Classroom Details | 00:00:00 | ||
| Video3_Issues_with_Mean Details | 00:00:00 | ||
| Video4_Median Details | 00:00:00 | ||
| Video5_Variance_and_SD Details | 00:00:00 | ||
| Video6_Percentiles Details | 00:00:00 | ||
| Video7_Percentile_Interpretation Details | 00:00:00 | ||
| Video8_Outliers_Detection Details | 00:00:00 | ||
| Video9_Box_Plots Details | 00:00:00 | ||
| Video10_Box_Plots_Example Details | 00:00:00 | ||
| Video11_Conclusion Details | 00:00:00 | ||
| Video12_Assignment Details | 00:00:00 | ||
| Assignment 1 discussion | |||
| Assignment_1 data manipulation AirBNB NY Details | 00:00:00 | ||
| Session-5 Data Cleaning | |||
| Video 1 _steps_in_model_building Details | 00:00:00 | ||
| Video 2_credit_risk_data Details | 00:00:00 | ||
| Video 3_data_dictionary Details | 00:00:00 | ||
| Video 4_basic_contents Details | 00:00:00 | ||
| Video 5_discrete_continuous_variable Details | 00:00:00 | ||
| Video 6_discrete_variable_exploration Details | 00:00:00 | ||
| Video7_Continuous_variable_Exploration Details | 00:00:00 | ||
| Video8_Data_Cleaning Details | 00:00:00 | ||
| Video9_Data_Cleaning_Scenario1 Details | 00:00:00 | ||
| Video10_Data_Cleaning_Scenario2.mp4 Details | 00:00:00 | ||
| Video11_Data_Cleaning_Scenario3 Details | 00:00:00 | ||
| Video12_Data_Cleaning_Assignment Details | 00:00:00 | ||
| Session-6 Regression_analysis | |||
| Video1_Correlation Details | 00:00:00 | ||
| Video2_Regression Details | 00:00:00 | ||
| Video3_Least_Squares Details | 00:00:00 | ||
| Video4_Regression_Code_Python Details | 00:00:00 | ||
| Video5_R_Squared Details | 00:00:00 | ||
| Video6_Multiple_Regression Details | 00:00:00 | ||
| Video7_P_value Details | 00:00:00 | ||
| Video8_Adjusted_R_Squared Details | 00:00:00 | ||
| Video9_Inter_Relation_Between_Variables Details | 00:00:00 | ||
| Video10_Multicollinearity Details | 00:00:00 | ||
| Video11_VIF Details | 00:00:00 | ||
| Video12_Steps_in_Building_Linear_Reg_line Details | 00:00:00 | ||
| Session-7 logistic_regression | |||
| Video1_Linear_Reg_Sk_learn Details | 00:00:00 | ||
| Video2_Issues_Linear_Regression Details | 00:00:00 | ||
| Video3_Logistic_Regression Details | 00:00:00 | ||
| Video4_Logistic_Reg_model Details | 00:00:00 | ||
| Video5_Confusion_matrix Details | 00:00:00 | ||
| Video6_VIF Details | 00:00:00 | ||
| Video7_P_value Details | 00:00:00 | ||
| Video8_Rank_order_Variables Details | 00:00:00 | ||
| Video9_Steps_In_building_the_Logistic_Reg_model Details | 00:00:00 | ||
| Video10_Conclusion Details | 00:00:00 | ||
| Assignment_3 data Cleaning -Credit data | |||
| Assignment3 Data Cleaning credit Details | 00:00:00 | ||
| Session-8 decision _ trees | |||
| Video1_Decision_tree_Business_problem Details | 00:00:00 | ||
| Video2_Decision_tree_Approach Details | 00:00:00 | ||
| Video3_Segmentation_using_variable Details | 00:00:00 | ||
| Video4_Entropy Details | 00:00:00 | ||
| Video5_information_gain Details | 00:00:00 | ||
| Video6_Decision_tree_algorithm Details | 00:00:00 | ||
| Video7_Decision_tree_in_Python Details | 00:00:00 | ||
| Video8_Decision_tree_result Details | 00:00:00 | ||
| Video9_Rules_and_Predictions Details | 00:00:00 | ||
| Video10_tree_validation Details | 00:00:00 | ||
| Video11_Problem_of_Overfitting Details | 00:00:00 | ||
| Video12_Pruning Details | 00:00:00 | ||
| Video13_underfitting Details | 00:00:00 | ||
| Video14_Finetuning_pruning_parameters Details | 00:00:00 | ||
| Video15_Steps_in_building_DT_model Details | 00:00:00 | ||
| Video16_Decision_trees_vs_logistic_reg Details | 00:00:00 | ||
| Session-9 model selection cross validation | |||
| Video1_Steps_in_model_building Details | 00:00:00 | ||
| Video2_Regression_validation Details | 00:00:00 | ||
| Video3_Class_wise_Accuracy Details | 00:00:00 | ||
| Video4_Sensitivity_Specificity Details | 00:00:00 | ||
| Video5_Threshold Details | 00:00:00 | ||
| Video6_Recall_Precision Details | 00:00:00 | ||
| Video7_ROC_AUC Details | 00:00:00 | ||
| Video8_OverSamping_UnderSampling Details | 00:00:00 | ||
| Video9_Cross_Validation Details | 00:00:00 | ||
| Video10_TenFold_Cross_validation Details | 00:00:00 | ||
| Video11_Conclusion_ Details | 00:00:00 | ||
| Session 10 feature_engineering | |||
| Video1_What_is_Feature_Engineering Details | 00:00:00 | ||
| Video2_basic_model Details | 00:00:00 | ||
| Video3_Date_Features Details | 00:00:00 | ||
| Video4_Gelo_Location Details | 00:00:00 | ||
| Video5_Transformations Details | 00:00:00 | ||
| Video6_One_hot_Encoding Details | 00:00:00 | ||
| Video7_Conclusion.. Details | 00:00:00 | ||
| Assignment | |||
| Discussion Car_Dekho_pricing_Regression_V1 Details | 00:00:00 | ||
| SESSION 11 Random Forest | |||
| Video1_Wisdom_Of_Crowd Details | 00:00:00 | ||
| Video2_Ensemble_Learning Details | 00:00:00 | ||
| Video3_Bagging Details | 00:00:00 | ||
| Video4_Random_Forest Details | 00:00:00 | ||
| Video5_Hyperparameters_in_RF Details | 00:00:00 | ||
| Video6_Why_Random_Forest_Works Details | 00:00:00 | ||
| Video7_Case_Study_RF Details | 00:00:00 | ||
| Video8_Random_Forest_Results Details | 00:00:00 | ||
| Video9_How_to_finetune_hyperparameters Details | 00:00:00 | ||
| SESSION 12 Boosting | |||
| Video1_Boosting Details | 00:00:00 | ||
| Video2_Boosting_Parameters Details | 00:00:00 | ||
| Video3_Boosting_Case_Study Details | 00:00:00 | ||
| Video4_Boosting_Results Details | 00:00:00 | ||
| Video5_Boosting_Conclusion Details | 00:00:00 | ||
| SESSION 13 NLP_DATA_PRE_PROCESSION | |||
| Video1_NLP_introuction Details | 00:00:00 | ||
| Video2_NLP_Terminology Details | 00:00:00 | ||
| Video3_Data_Cleaning_Steps Details | 00:00:00 | ||
| Video4_Lower_Case_Conversion Details | 00:00:00 | ||
| Video5_Tokenizing Details | 00:00:00 | ||
| Video6_Contra_to_Expansion Details | 00:00:00 | ||
| Video7_Stopwords_Removal Details | 00:00:00 | ||
| Video8_RegEx Details | 00:00:00 | ||
| Video9_Spelling.mp4 Details | 00:00:00 | ||
| Video10_Lemmatization Details | 00:00:00 | ||
| Video11_Word_Cloud Details | 00:00:00 | ||
| Video12_Single_Preprocessing_Function Details | 00:00:00 | ||
| Video13_DTM Details | 00:00:00 | ||
| SESSION 14 NLP_SENTIMENT_ANALYSIS | |||
| Video1_Introduction_ Details | 00:00:00 | ||
| Video2_Data_Preparation Details | 00:00:00 | ||
| Video3_Naive_Bayes_Model Details | 00:00:00 | ||
| Video4_Sentiment_Analysis_Application Details | 00:00:00 | ||
| SESSION 15 Interview Preparation | |||
| Interview_Preparations_steps Details | 00:00:00 | ||
| ASSIGNMENT 6 Credit Risk Logistic Regression | |||
| Assignment_6 Credit Risk Logistic Model Details | 00:00:00 | ||
| SESSION 16 DRIVER ANALYSIS | |||
| Video1_Introduction 20th Feb 2021 Details | 00:00:00 | ||
| Video2_Continuous_Variables_Exploration Details | 00:00:00 | ||
| Video3_Categorical_Variables_Exploration Details | 00:00:00 | ||
| Video4_Continuous_Vs_Continuous_Variables Details | 00:00:00 | ||
| Video5_Continuous_Vs_Categorical_Variables Details | 00:00:00 | ||
| Video6_Information_Value_IV Details | 00:00:00 | ||
| Video7_Information_Gain_IG Details | 00:00:00 | ||
| Video8_Categorical_VS_Continuous Details | 00:00:00 | ||
