Complete Machine Learning playlist
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What you'll learn
This course includes
- 36.5 hours of video
- Certificate of completion
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Course content
1 modules • 98 lessons • 36.5 hours of video
Complete Machine Learning playlist
98 lessons
• 23.5 hours
Complete Machine Learning playlist
98 lessons
• 23.5 hours
- Complete Roadmap To Follow To Prepare Machine Learning With All Videos And Materials 18:56
- Tutorial 22-Univariate, Bivariate and Multivariate Analysis- Part1 (EDA)-Data Science 13:11
- Tutorial 23-Univariate, Bivariate and Multivariate Analysis- Part2 (EDA)-Data Science 15:53
- Tutorial 24- Histogram in EDA- Data Science 04:42
- Tutorial 24-Z Score Statistics Data Science 11:59
- Tutorial 25- Probability Density function and CDF- EDA-Data Science 07:52
- Tutorial 26- Linear Regression Indepth Maths Intuition- Data Science 24:15
- Tutorial 27- Ridge and Lasso Regression Indepth Intuition- Data Science 20:17
- Tutorial 28- Ridge and Lasso Regression using Python and Sklearn 09:51
- Multiple Linear Regression using python and sklearn 19:51
- Tutorial 28-MultiCollinearity In Linear Regression- Part 2 16:00
- Machine Learning-Bias And Variance In Depth Intuition| Overfitting Underfitting 16:53
- Tutorial 29-R square and Adjusted R square Clearly Explained| Machine Learning 17:16
- Tutorial 31- Hypothesis Test, Type 1 Error, Type 2 Error 11:45
- What Is P Value In Statistics In Simple Language? 11:18
- Tutorial 32- All About P Value,T test,Chi Square Test, Anova Test and When to Use What? 12:01
- Tutorial 33- P Value,T test, Correlation Implementation with Python- Hypothesis Testing 20:02
- Tutorial 33- Chi Square Test Implementation with Python- Hypothesis Testing- Part 2 14:09
- Tutorial 34- Performance Metrics For Classification Problem In Machine Learning- Part1 24:12
- Tutorial 35- Logistic Regression Indepth Intuition- Part 1| Data Science 12:40
- Tutorial 36- Logistic Regression Indepth Intuition- Part 2| Data Science 28:17
- Tutorial 36- Logistic Regression Mutliclass Classification(OneVsRest)- Part 3| Data Science 06:39
- Tutorial 37: Entropy In Decision Tree Intuition 08:58
- Tutorial 38- Decision Tree Information Gain 12:40
- Tutorial 39- Gini Impurity Intuition In Depth In Decision Tree 11:13
- Tutorial 40- Decision Tree Split For Numerical Feature 06:11
- Tutorial 41-Performance Metrics(ROC,AUC Curve) For Classification Problem In Machine Learning Part 2 09:49
- Performance Metrics On MultiClass Classification Problems 06:02
- K Nearest Neighbor classification with Intuition and practical solution 20:06
- K Nearest Neighbour Easily Explained with Implementation 18:02
- What is AdaBoost (BOOSTING TECHNIQUES) 14:06
- Visibility Climate Prediction- You Can Add This In Your Resume 17:23
- Euclidean Distance and Manhattan Distance 08:39
- Silhouette (clustering)- Validating Clustering Models- Unsupervised Machine Learning 20:07
- Dimensional Reduction| Principal Component Analysis 19:06
- Tutorial 42-How To Find Optimal Threshold For Binary Classification - Data Science 15:10
- Tutorial 47- Bayes' Theorem| Conditional Probability- Machine Learning 11:02
- Tutorial 48- Naive Bayes' Classifier Indepth Intuition- Machine Learning 15:55
- Tutorial 49- How To Apply Naive Bayes' Classifier On Text Data (NLP)- Machine Learning 13:10
- Support Vector Machine (SVM) Basic Intuition- Part 1| Machine Learning 12:50
- Maths Intuition Behind Support Vector Machine Part 2 | Machine Learning Data Science 23:27
- SVM Kernels In-depth Intuition- Polynomial Kernels Part 3 | Machine Learning Data Science 20:41
- SVM Kernal- Polynomial And RBF Implementation Using Sklearn- Machine Learning 14:40
- Gradient Boosting In Depth Intuition- Part 1 Machine Learning 11:20
- Gradient Boosting Complete Maths Indepth Intuiton Explained| Machine Learning- Part2 17:47
- Xgboost Classification Indepth Maths Intuition- Machine Learning Algorithms🔥🔥🔥🔥 23:59
- Xgboost Regression In-Depth Intuition Explained- Machine Learning Algorithms 🔥🔥🔥🔥 19:30
- Data Science In Medical-Live Tracking Of CO--VID Cases In India using Python 15:39
- Perform EDA In Seconds With Visualization Using SweetViz Library 17:20
- 4 End To End Projects Till Deployment For Beginners In Data Science| All You Have To Do Is Learn 10:49
- Deploy Machine Learning Models Using StreamLit Library- Data Science 12:56
- Perform Exploratory Data Analysis In Minutes- Data Science| Machine Learning 18:34
- Pandas Visual Analysis- Perform Exploratory Data Analysis In A Single Line Of Code🔥🔥🔥🔥 13:12
- How To Read And Process Huge Datasets in Seconds Using Vaex Library| Data Science| Machine Learning 19:31
- D-Tale The Best Library To Perform Exploratory Data Analysis Using Single Line Of Code🔥🔥🔥🔥 12:54
- Interview Prep Day3-How To Prepare Support Vector Machines Important Questions In Interviews🔥🔥 13:45
- Google Datasets Search Engine- Search All Datasets From One Place For Data Science,Machine Learning 11:51
- How To Run Flask In Google Colab 07:39
- Time Series Forecasting Using Facebook FbProphet 16:57
- Performance Metrics Interview Questions- Data Science 04:34
- How To Perform Post Pruning In Decision Tree? Prevent Overfitting- Data Science 16:24
- How To Train Machine Learning Model Using CPU Multi Cores 14:41
- Step By Step Process To Learn Machine Learning Algorithm Efficiently 14:08
- Data Science Is Just Not About Model Building 07:59
- How To Interpret The ML Model? Is Your Model Black Box? Lime Library 11:27
- 6 Healthcare End To End Machine Learning Projects- Credits Devansh and Bedanta 07:48
- Overfitting, Underfitting And Data Leakage Explanation With Simple Example 14:12
- What Is API? Application Programming Interface And Why It Is Important-Data Science 08:25
- TextBlob Library In Python For Natural Language Processing 08:53
- Introduction To MLflow-An Open Source Platform for the Machine Learning Lifecycle 12:13
- Amazing Data Science End To End Project From Starters In ML and Deep Learning- Agriculture Domain 08:16
- Lux - Python Library for Intelligent Visual Discovery 10:11
- Texthero-Text Preprocessing, Representation And Visualization From Zero to Hero. 15:58
- Rainfall Prediction- Converting A Kaggle Project to End To End Machine Learning Project 06:50
- PyWebIO- Creating WebAPP Using Python Without Using HTML And JS 17:18
- Creating BMI Calculator Web APP Using Python And PyWebIO 12:11
- Deployment Of ML Models Using PyWebIO And Flask 12:28
- Shapash- Python Library To Make Machine Learning Interpretable 16:03
- Difference Between fit(), transform(), fit_transform() and predict() methods in Scikit-Learn 26:03
- EvalML AutoML Library To Automate Feature Engineering, Feature Selection,Model Creation And Tuning 23:28
- Lazy Predict Python- Understanding Which Models Works Well Without Any Tuning 09:05
- How To Automate NLP Tasks Using EvalML Library 15:28
- Deployment Of ML Models Using PyWebIO And Flask In Heroku 07:33
- All Automated EDA Libraries All At One Place 14:39
- Discussing All The Types Of Feature Transformation In Machine Learning 22:24
- Automating Web Scrapping Using AutoScraper Library 15:33
- Automating WebScraping Amazon Ecommerce Website Using AutoScrapper 14:14
- AutoScraper and Flask: Create an API From Amazon Website in Less Than 10 Minutes 14:13
- Autoviz-Automatically Visualize Any Dataset With Single Line Of Code 06:10
- AutoScraper- Scrap Images From Amazon Ecommerce- End To End Web Scraping Application 06:55
- All Type Of Cross Validation With Python All In 1 Video 15:23
- DataPrep Library- Perform Faster EDA Within No Time 08:42
- Time Series Forecasting Made Easy Using Dart Library - Perform Multivariate Forecasting In No Time 11:37
- FLAML - Fast and Lightweight AutoML Library By Microsoft 07:32
- Definition Of Bias And Variance In Machine Learning- Interview Question 08:18
- Elasticnet Regression Machine Learning Algorithm Explained In Depth 11:04
- Out Of Bag Evaluation(OOB) And OOB Score Or Error In Random Forest 07:11
- PCA Indepth Geometric And Mathematical InDepth Intuition ML Algorithms 01:28:31
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