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| 1. 1. How to download Kaggle data in Google Collab!.mp4 |
27.64Мб |
| 1. 1. Introducing Fraud Detection and Conducting Exploratory Data Analysis..mp4 |
35.13Мб |
| 1. 1. Introduction..mp4 |
33.71Мб |
| 1. 1. Introduction to Big Data Analytics and Apache Spark..mp4 |
32.74Мб |
| 1. 1. Introduction to Customer Churn Prediction..mp4 |
29.45Мб |
| 1. 1. Introduction to House Prices Prediction..mp4 |
104.11Мб |
| 1. 1. Introduction to Predictive Modeling and Machine Learning..mp4 |
29.13Мб |
| 1. 1. Introduction to Sentiment Analysis & NLP..mp4 |
80.64Мб |
| 1. 1. Reading and Preprocessing Data..mp4 |
37.57Мб |
| 1. 1. Visual Exploring of Google App Store Data..mp4 |
60.87Мб |
| 1. Introduction.mp4 |
74.22Мб |
| 2. 2. Big Data Data Exploration and Preprocessing..mp4 |
29.88Мб |
| 2. 2. Creating Directories & The images data..mp4 |
27.76Мб |
| 2. 2. Data Cleaning and Preprocessing of Google App Store Data..mp4 |
46.12Мб |
| 2. 2. Data Exploration and Preprocessing of the Titanic Dataset..mp4 |
42.42Мб |
| 2. 2. Data Preprocessing and Cleaning..mp4 |
23.38Мб |
| 2. 2. Data Transformation and Visualization..mp4 |
29.67Мб |
| 2. 2. Feature Selection and Model Building..mp4 |
39.10Мб |
| 2. 2. Housing Data Processing & Cleaning For ML Model..mp4 |
123.77Мб |
| 2. 2. Model Building for Fraud Detection..mp4 |
42.67Мб |
| 2. 2. Text Preprocessing for Sentiment Analysis..mp4 |
108.92Мб |
| 3. 3. Advanced Techniques for Churn Prediction..mp4 |
51.02Мб |
| 3. 3. Advanced Techniques for Fraud Detection..mp4 |
102.99Мб |
| 3. 3. Big Data Transformation and Feature Engineering..mp4 |
27.60Мб |
| 3. 3. Data Visualization Techniques..mp4 |
96.99Мб |
| 3. 3. Doing EDA (Exploratory Data Analysis) Using Data Visualization..mp4 |
33.43Мб |
| 3. 3. Feature Extraction for Sentiment Analysis..mp4 |
78.34Мб |
| 3. 3. Image data preprocessing and visualization with Python..mp4 |
29.04Мб |
| 3. 3. Model Selection and Evaluation of The Titanic Dataset..mp4 |
31.30Мб |
| 3. 3. Train-Test Split and Model Selection..mp4 |
41.57Мб |
| 3. 3. Visualizing Time Series Data..mp4 |
30.23Мб |
| 4. 4. Big Data Visualization and Analysis..mp4 |
27.31Мб |
| 4. 4. Building and Evaluating Forecasting Models..mp4 |
48.36Мб |
| 4. 4. Building Model for the Housing Data..mp4 |
19.84Мб |
| 4. 4. Building Sentiment Analysis Models..mp4 |
29.82Мб |
| 4. 4. Creating and Validating Model using CNN..mp4 |
46.16Мб |
| 4. 4. Ensemble Methods and Model Evaluation..mp4 |
30.32Мб |
| 4. 4. Model Evaluation and Interpretability..mp4 |
33.84Мб |
| 4. 4. Model Training and Hyperparameter Tuning of The Titanic Dataset..mp4 |
59.48Мб |
| 4. 4. Model Training with XGBoost..mp4 |
30.68Мб |
| 4. 4. Statistical Analysis and Hypothesis Testing..mp4 |
49.78Мб |
| 5. 5. Conclusion and Next Steps..mp4 |
37.73Мб |
| 5. 5. Data Storytelling..mp4 |
51.70Мб |
| 5. 5. Deployment of The Predictive Models of The Titanic Dataset..mp4 |
61.46Мб |
| 5. 5. Evaluation of Sentiment Analysis Models..mp4 |
38.87Мб |
| 5. 5. Making Predictions and Submission..mp4 |
19.35Мб |
| 5. 5. Model Deployment..mp4 |
32.61Мб |
| 5. 5. Model Interpretation, Deployment, and Next steps..mp4 |
26.96Мб |
| 5. 5. Predicting Future Bitcoin Prices..mp4 |
53.39Мб |
| 5. 5. Validating Our Model..mp4 |
28.96Мб |
| 6. 6. Conclusion..mp4 |
66.60Мб |
| Bonus Resources.txt |
386б |
| Get Bonus Downloads Here.url |
183б |