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Название Machine Learning & Data Science with Python, Kaggle & Pandas
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1. Accessing and Making Files Available.mp4 34.62Мб
1. Adding Columns to Pandas Data Frames.mp4 33.58Мб
1. Classification vs Regression in Machine Learning.mp4 19.91Мб
1. Competitions on Kaggle Lesson 1.mp4 188.20Мб
1. Concatenating Pandas Dataframes Concat Function.mp4 63.88Мб
1. Courses in Kaggle.mp4 52.16Мб
1. Creating a Pandas Series with a List.mp4 39.20Мб
1. Creating NumPy Array with The Array() Function.mp4 29.49Мб
1. Creating Pandas DataFrame with List.mp4 22.56Мб
1. Datasets on Kaggle.mp4 133.21Мб
1. Decision Tree Algorithm Theory.mp4 35.76Мб
1. Dropping Columns with Low Correlation.mp4 26.82Мб
1. Element Selection Operations in Pandas DataFrames Lesson 1.mp4 29.88Мб
1. Examining Missing Values.mp4 45.78Мб
1. Examining the Code Section in Kaggle Lesson 1.mp4 79.55Мб
1. Examining the Data Set 3.mp4 39.12Мб
1. First Step to the Project.mp4 117.19Мб
1. Hierarchical Clustering Algorithm Theory.mp4 28.57Мб
1. Hyperparameter Optimization Theory.mp4 33.15Мб
1. Indexing Numpy Arrays.mp4 26.60Мб
1. Installing Anaconda Distribution for Windows.mp4 118.30Мб
1. Introduction to NumPy Library.mp4 45.30Мб
1. Introduction to Pandas Library.mp4 33.93Мб
1. K-Fold Cross-Validation Theory.mp4 17.46Мб
1. K Means Clustering Algorithm Theory.mp4 17.14Мб
1. K Nearest Neighbors Algorithm Theory.mp4 28.67Мб
1. Linear Regression Algorithm Theory in Machine Learning A-Z.mp4 34.06Мб
1. Loading a Dataset from the Seaborn Library.mp4 37.72Мб
1. Logistic Regression.mp4 29.34Мб
1. Machine Learning & Data Science with Kaggle, Pandas , Numpy.html 266б
1. Multi-Index and Index Hierarchy in Pandas DataFrames.mp4 42.66Мб
1. Numeric Variables (Analysis with Distplot) Lesson 1.mp4 80.40Мб
1. Numeric Variables – Target Variable (Analysis with FacetGrid) Lesson 1.mp4 49.34Мб
1. Operations with Comparison Operators.mp4 21.17Мб
1. Principal Component Analysis (PCA) Theory.mp4 37.95Мб
1. Project Conclusion and Sharing.mp4 28.65Мб
1. Random Forest Algorithm Theory.mp4 22.89Мб
1. Required Python Libraries.mp4 63.57Мб
1. Reshaping a NumPy Array Reshape() Function.mp4 26.15Мб
1. Support Vector Machine Algorithm Theory.mp4 21.84Мб
1. Unsupervised Learning Overview.mp4 16.92Мб
1. User Page Review on Kaggle.mp4 81.57Мб
1. What is Bias Variance Trade-Off.mp4 55.04Мб
1. What is Discussion on Kaggle.mp4 40.65Мб
1. What is Kaggle.mp4 129.75Мб
1. What is Logistic Regression Algorithm in Machine Learning.mp4 27.84Мб
1. What is Machine Learning.mp4 27.58Мб
1. What is Supervised Learning in Machine Learning.mp4 31.69Мб
1. What is the Recommender System Part 1.mp4 23.02Мб
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10. Feature Scaling with the Robust Scaler Method for Machine Learning Algorithms.mp4 11.46Мб
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2. Competitions on Kaggle Lesson 2.mp4 191.71Мб
2. Creating a Pandas Series with a Dictionary.mp4 18.29Мб
2. Creating NumPy Array with Zeros() Function.mp4 24.06Мб
2. Creating Pandas DataFrame with NumPy Array.mp4 12.10Мб
2. Cross Validation.mp4 30.21Мб
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2. Decision Tree Algorithm with Python Part 1.mp4 31.54Мб
2. Element Selection in Multi-Indexed DataFrames.mp4 24.59Мб
2. Element Selection Operations in Pandas DataFrames Lesson 2.mp4 31.83Мб
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2. Examining the Data Set 1.mp4 42.88Мб
2. Examining Unique Values.mp4 44.56Мб
2. FAQ about Kaggle.html 10.94Кб
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2. Hierarchical Clustering Algorithm with Python Part 1.mp4 35.51Мб
2. Hyperparameter Optimization with Python.mp4 47.47Мб
2. Identifying the Largest Element of a Numpy Array.mp4 15.14Мб
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2. K Nearest Neighbors Algorithm with Python Part 1.mp4 35.05Мб
2. Linear Regression Algorithm With Python Part 1.mp4 76.18Мб
2. Loading the Dataset.mp4 9.99Мб
2. Logistic Regression Algorithm with Python Part 1.mp4 72.23Мб
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2. Numeric Variables – Target Variable (Analysis with FacetGrid) Lesson 2.mp4 35.62Мб
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2. Principal Component Analysis (PCA) with Python Part 1.mp4 26.02Мб
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2. Random Forest Algorithm with Pyhon Part 1.mp4 38.59Мб
2. Ranking Among Users on Kaggle.mp4 107.00Мб
2. Removing Rows and Columns from Pandas Data frames.mp4 15.57Мб
2. Slicing One-Dimensional Numpy Arrays.mp4 22.29Мб
2. Support Vector Machine Algorithm with Python Part 1.mp4 35.56Мб
2. The Power of NumPy.mp4 59.87Мб
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3. Categoric Variables – Target Variable (Analysis with Count Plot) Lesson 1.mp4 24.12Мб
3. Creating NumPy Array with Ones() Function.mp4 15.84Мб
3. Creating Pandas DataFrame with Dictionary.mp4 15.83Мб
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3. Data Entry with Excel Files.mp4 21.83Мб
3. Dealing with Outliers – Trtbps Variable Lesson 1.mp4 42.84Мб
3. Decision Tree Algorithm with Python Part 2.mp4 48.97Мб
3. Detecting Least Element of Numpy Array Min(), Ar.mp4 10.19Мб
3. Evaluating Performance Regression Error Metrics in Python.mp4 45.71Мб
3. Examining the Code Section in Kaggle Lesson 3.mp4 159.82Мб
3. Hierarchical Clustering Algorithm with Python Part 2.mp4 28.90Мб
3. Initial analysis on the dataset.mp4 63.98Мб
3. Installing Anaconda Distribution for MacOs.mp4 46.34Мб
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3. Random Forest Algorithm with Pyhon Part 2.mp4 38.74Мб
3. Registering on Kaggle and Member Login Procedures.mp4 43.55Мб
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4. Decision Tree Algorithm with Python Part 3.mp4 14.71Мб
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5. Getting to Know the Kaggle Homepage.mp4 122.88Мб
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