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Decision_Trees_Implementation_(Classification_and_Regression).ipynb
Decision_Trees_Implementation_(Classification_and_Regression).ipynb
 
 
Logistic_Regression_Boston_Data_binning.ipynb
Logistic_Regression_Boston_Data_binning.ipynb
 
 
ML_01_Introduction_To_Machine_Learning.ipynb
ML_01_Introduction_To_Machine_Learning.ipynb
 
 
ML_02_Machine_Learning_Basics.ipynb
ML_02_Machine_Learning_Basics.ipynb
 
 
ML_03_Linear_Regression_part1.ipynb
ML_03_Linear_Regression_part1.ipynb
 
 
ML_04_Linear_Regression_Part2_Assumption_Checks.ipynb
ML_04_Linear_Regression_Part2_Assumption_Checks.ipynb
 
 
ML_05_Linear_Regression_Implementation(Part3)_ipynb.ipynb
ML_05_Linear_Regression_Implementation(Part3)_ipynb.ipynb
 
 
ML_06_Evaluation__Metrics_For_regression.ipynb
ML_06_Evaluation__Metrics_For_regression.ipynb
 
 
ML_08_Ridge_Vs_Lasso_Vs_Elastic(Regularization).ipynb
ML_08_Ridge_Vs_Lasso_Vs_Elastic(Regularization).ipynb
 
 
ML_09_Classification_in_Machine_Learning(Logistic_Regression).ipynb
ML_09_Classification_in_Machine_Learning(Logistic_Regression).ipynb
 
 
ML_10_Logistic_Regression_Implementation.ipynb
ML_10_Logistic_Regression_Implementation.ipynb
 
 
ML_10_Logistic_Regression_Implementation_1.ipynb
ML_10_Logistic_Regression_Implementation_1.ipynb
 
 
ML_11_Evaluation_Metrics_For_Classification.ipynb
ML_11_Evaluation_Metrics_For_Classification.ipynb
 
 
ML_12_Decision_Trees_Theory.ipynb
ML_12_Decision_Trees_Theory.ipynb
 
 
ML_13_Decision_Tree_Implementation(Regressor_and_Classifier).ipynb
ML_13_Decision_Tree_Implementation(Regressor_and_Classifier).ipynb
 
 
ML_14_Basic_Ensemble_Techniques.ipynb
ML_14_Basic_Ensemble_Techniques.ipynb
 
 
ML_15_Advanced_Ensemble_Techniques(Stacking).ipynb
ML_15_Advanced_Ensemble_Techniques(Stacking).ipynb
 
 
ML_16_Advanced_Ensemble_Techniques(Blending).ipynb
ML_16_Advanced_Ensemble_Techniques(Blending).ipynb
 
 
ML_17_Advanced_Ensemble_Techniques(Bagging)(Random_Forest).ipynb
ML_17_Advanced_Ensemble_Techniques(Bagging)(Random_Forest).ipynb
 
 
ML_18_Advanced_Ensemble_Techniques(Boosting)(XGBoost).ipynb
ML_18_Advanced_Ensemble_Techniques(Boosting)(XGBoost).ipynb
 
 
ML_19_K_Nearest_Neighbors.ipynb
ML_19_K_Nearest_Neighbors.ipynb
 
 
ML_20_Naive Bayes Algorithm.ipynb
ML_20_Naive Bayes Algorithm.ipynb
 
 
ML_20_Naive_Bayes_Algorithm_theory.ipynb
ML_20_Naive_Bayes_Algorithm_theory.ipynb
 
 
ML_21_Support_Vector_Machine(SVM_SVC).ipynb
ML_21_Support_Vector_Machine(SVM_SVC).ipynb
 
 
ML_22_Handling_Imbalanced_Data.ipynb
ML_22_Handling_Imbalanced_Data.ipynb
 
 
ML_23_Cross_Validation_and_Hyperparameter_Tuning.ipynb
ML_23_Cross_Validation_and_Hyperparameter_Tuning.ipynb
 
 
ML_24_Unsupervised_Learning_algorithms_(PCA).ipynb
ML_24_Unsupervised_Learning_algorithms_(PCA).ipynb
 
 
ML_25_Principal_Component_Analysis.ipynb
ML_25_Principal_Component_Analysis.ipynb
 
 
ML_26_Anomaly_Detection_Using_Isolation_Forest.ipynb
ML_26_Anomaly_Detection_Using_Isolation_Forest.ipynb
 
 
ML_27_K_Means_Clustering_Algorithm.ipynb
ML_27_K_Means_Clustering_Algorithm.ipynb
 
 
ML_28_K_Means_Clustering(Extra_Material)_.ipynb
ML_28_K_Means_Clustering(Extra_Material)_.ipynb
 
 
ML_29_Hierarchical_Clustering.ipynb
ML_29_Hierarchical_Clustering.ipynb
 
 
ML_Advanced_Ensemble_Techniques.ipynb
ML_Advanced_Ensemble_Techniques.ipynb
 
 
Neural_Network_Regression_Signal_Strength_Data.ipynb
Neural_Network_Regression_Signal_Strength_Data.ipynb
 
 
README.md
README.md
 
 
Support_Vector_Machine_Data_of_US_Airline_tweets.ipynb
Support_Vector_Machine_Data_of_US_Airline_tweets.ipynb
 
 
Twitter_Sentiment_Analysis.ipynb
Twitter_Sentiment_Analysis.ipynb
 
 
Unsupervised_Learning_Algorithms_(PCA)_.ipynb
Unsupervised_Learning_Algorithms_(PCA)_.ipynb
 
 

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Machine_Learning_Data_Science

Machine Learning is a field of study that gives computers the capability to learn without being explicitly programmed. Machine Learning is applied using Algorithms to process the data and get trained for delivering future predictions without human intervention. The inputs for Machine Learning are the set of instructions or data or observations. Machine Learning is used extensively by companies like Facebook, Google, etc.

image image Machine learning is a branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy

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