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Free Data Science Course Online - OSEMN Framework | Introduction
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Machine Learning and Deep Learning Bootcamp Series
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- 1 Free Data Science Course Online - OSEMN Framework | Introduction
- 2 Free Data Science Course Online - OSEMN Framework | Requirement Gathering in Data Science
- 3 Data Science Awesome Framework (Data Extraction Primer) - Step 2 | Data Extraction in ML
- 4 MongoDB in 25 minutes (Machine Learning) | Extract Data from NoSQL DB MongoDB for Machine Learning
- 5 Hands-on with Web Scraping using Python and Beautifulsoup | Data Extraction for Machine Learning
- 6 How to Extract Data using API | What is an API and How exactly it works | Python Code Part 1
- 7 How to Extract Data using API | What is an API and How exactly it works | Python Code Part 2
- 8 Load or Extract Data from MySQL DB or CSV file for ML | Extract Data using Sklearn Python for ML
- 9 Simulate Machine Learning Classification Data | Data Simulation Technique using Python
- 10 Simulate Machine Learning Regression & Clustering Data | Data Simulation Technique using Python
- 11 Scrubbing or Cleaning Bad data in Data Science (Python) - Step 3 | Data Munging in Machine Learning
- 12 3.Dataset Missing Values & Imputation (Detailed Python Tutorial) | Impute Missing values in ML
- 13 4.One Hot Encoding to process Categorical variables (Python) | Process Categorical Features
- 14 5.Split data into Training and Test set in Data Science (Python) | Train Test Split function in ML
- 15 6.Feature Scaling in Machine Learning(Normalization & Standardization) | Feature Scaling Sklearn
- 16 7.Outlier Detection and Treatment using Python - Part 1 | How to Detect outliers in Machine Learning
- 17 8.Outlier Detection and Treatment using Python - Part 2 | How to Detect outliers in Machine Learning
- 18 9.Outlier Detection and Treatment using Python - Part 3 | How to Detect outliers in Machine Learning
- 19 Log Transformation for Outliers | Convert Skewed data to Normal Distribution
- 20 Outlier Treatment through Square Root Transformation | Convert Skewed data to Normal Distribution
- 21 Python Pandas Tutorial Series: Using Map, Apply and Applymap
- 22 Use Regular Expression to split string into Dataframe columns (Pandas)
- 23 Python Pandas Tutorial - Adding & Dropping columns (Machine Learning)
- 24 Python Pandas Tutorial - Merge Dataframes (Machine Learning)
- 25 Python Exploratory Data Analysis (OSEMN Framework) - Step 4
- 26 Univariate Analysis for Categorical Variables using Python
- 27 Univariate Analysis for Numerical Variables (Exploratory Data Analysis) Intuition
- 28 Convert Numerical variable to Categorical Intuition | BINNING
- 29 BINNING | Convert Numerical variable to Categorical using Python
- 30 How to do Bivariate Analysis of Numerical Numerical Variables
- 31 Chi Square Test | How to do Bivariate Analysis of Categorical Categorical Variables
- 32 z-test & t-test | Bivariate Analysis for Numerical-Categorical Variables
- 33 Bivariate Analysis for Numerical-Categorical Variables|ANOVA|Data Science EDA
- 34 Don't know the Difference among AI, ML and Deep Learning ?
- 35 Simple Linear Regression using Scikit Learn & Spark MLLib | Introduction & Intuition
- 36 Simple Linear Regression using Scikit Learn & Spark MLLib | Data Pre-processing | Code Part 1
- 37 Simple Linear Regression using Scikit Learn & Spark MLLib | Building Model | Code Part 2
- 38 Simple Linear Regression using Scikit Learn & Spark MLLib | Graphical Comparison | Code Part 3
- 39 Simple Linear Regression | Scikit Learn & Spark MLLib | Model Evaluation Techniques - Part 1
- 40 Simple Linear Regression | MSE RMSE & MAE | Model Evaluation Techniques - Part 2
- 41 Enable Apache Spark(Pyspark) to run on Jupyter Notebook - Part 1 | Install Spark on Jupyter Notebook
- 42 Enable Apache Spark(Pyspark) to run on Jupyter Notebook - Part 2 | Install Spark on Jupyter Notebook
- 43 Run PySpark on Google Colab for FREE! | PySpark on Jupyter
- 44 Simple Linear Regression using Spark MLLib | Introduction
- 45 Simple Linear Regression using Spark MLLib | Data Preprocessing
- 46 Simple Linear Regression using Spark MLLib | Build Train & Evaluate Model
- 47 Multiple Linear Regression using Scikit Learn | Introduction & Intuition
- 48 Multiple Linear Regression using Scikit Learn | Coding Part 1
- 49 Multiple Linear Regression using Scikit Learn | Coding Part 2
- 50 Multiple Linear Regression using Spark(PySpark) MLLib | Coding Part - 1
- 51 Multiple Linear Regression using Spark(PySpark) MLLib | Coding Part - 2
- 52 Multiple Linear Regression using Spark(PySpark) MLLib | Coding Part - 3
- 53 Polynomial Regression using Python | Polynomial Regression Machine Learning
- 54 Polynomial Regression Machine Learning Python Code
- 55 Decision Tree Regression Introduction and Intuition
- 56 Complete End to End Python code for Decision Tree Regression
- 57 Random Forest Regression Introduction and Intuition
- 58 Complete End to End Python code for Random Forest Regression
- 59 Fantastic Explanation of Logistic Regression in Machine Learning - Part 1
- 60 Fantastic Explanation of Logistic Regression Model - Part 2
- 61 How to Develop and Train Logistic Regression model on Titanic Dataset | Python Code Part 1
- 62 How to Develop and Train Logistic Regression model on Titanic Dataset | Python Code Part 2
- 63 Best Explanation of Confusion Matrix False Positive False Negative so far
- 64 Precision Recall and F1-Score Explanation in Easy way
- 65 How to use CAP curve for Classification Model Evaluation? | What is CAP Curve?
- 66 Best Explanation of Evaluating Classification Model using AUC-ROC Curve
- 67 How to Generate AUC-ROC curve for Evaluating Logistic Regression Model?
- 68 Fantastic Explanation of Support Vector Machine algorithm | Support Vector Machine Intuition
- 69 Build Train and Evaluate Support Vector Machine Model | Train & Evaluate SVM model using python
- 70 Fantastic Explanation of K-Nearest Neighbor | K-Nearest Neighbor Introduction and Intuition
- 71 Build Train & Evaluate K-Nearest Neighbor (KNN) Model | Using Python & Scikit Learn
- 72 Decision Tree Classification Introduction and Intuition
- 73 What are the 4 Key Steps to Create a Decision Tree? | How to Create Decision tree?
- 74 How to Measure the Purity of Decision Tree split using GINI INDEX | How to calculate Gini Index?
- 75 How to Measure the Purity of Decision Tree split using Information Gain
- 76 Build, Train & Evaluation Decision Tree Model | Decision Tree using Scikit Learn
- 77 How to Train Random Forest Classifier using Python? | How does Random Forest work?
- 78 How to AUTOMATE Data Science Lifecycle | How to AUTOMATE Machine Learning Pipeline
- 79 डेटा Science Lifecycle को स्वचालित कैसे करें | How to AUTOMATE Data Science Lifecycle in Hindi
