[GigaCourse.Com] Udemy - Machine Learning & Deep Learning in Python & R

• 26. ANN in R/8. Saving - Restoring Models and Using Callbacks.mp4-216.04 MB
• 36. Time Series - Preprocessing in Python/3. Time Series - Visualization in Python.mp4-165.19 MB
• 17. Ensemble technique 3 - Boosting/7. XGBoosting in R.mp4-161.3 MB
• 25. ANN in Python/9. Building Neural Network for Regression Problem.mp4-155.91 MB
• 25. ANN in Python/11. Saving - Restoring Models and Using Callbacks.mp4-151.58 MB
• 22. Creating Support Vector Machine Model in R/3. Classification SVM model using Linear Kernel.mp4-139.16 MB
• 26. ANN in R/6. Building Regression Model with Functional API.mp4-131.13 MB
• 26. ANN in R/3. Building,Compiling and Training.mp4-130.73 MB
• 33. Transfer Learning Basics/6. Project - Transfer Learning - VGG16.mp4-129.09 MB
• 7. Linear Regression/20. Ridge regression and Lasso in Python.mp4-128.84 MB
• 24. Neural Networks - Stacking cells to create network/3. Back Propagation.mp4-122.2 MB
• 37. Time Series - Important Concepts/5. Differencing in Python.mp4-113 MB
• 36. Time Series - Preprocessing in Python/5. Time Series - Feature Engineering in Python.mp4-112.69 MB
• 26. ANN in R/2. Data Normalization and Test-Train Split.mp4-111.78 MB
• 5. Introduction to Machine Learning/1. Introduction to Machine Learning.mp4-109.17 MB
• 36. Time Series - Preprocessing in Python/1. Data Loading in Python.mp4-108.86 MB
• 22. Creating Support Vector Machine Model in R/7. SVM based Regression Model in R.mp4-106.13 MB
• 7. Linear Regression/21. Ridge regression and Lasso in R.mp4-103.43 MB
• 13. Simple Decision Trees/13. Building a Regression Tree in R.mp4-103.33 MB
• 34. Transfer Learning in R/1. Project - Transfer Learning - VGG16 (Implementation).mp4-101.58 MB
• 36. Time Series - Preprocessing in Python/7. Time Series - Upsampling and Downsampling in Python.mp4-100.67 MB
• 6. Data Preprocessing/16. Bi-variate analysis and Variable transformation.mp4-100.39 MB
• 26. ANN in R/4. Evaluating and Predicting.mp4-99.28 MB
• 6. Data Preprocessing/8. EDD in R.mp4-96.98 MB
• 3. Setting up R Studio and R crash course/7. Creating Barplots in R.mp4-96.73 MB
• 7. Linear Regression/3. Assessing accuracy of predicted coefficients.mp4-92.11 MB
• 25. ANN in Python/10. Using Functional API for complex architectures.mp4-92.1 MB
• 17. Ensemble technique 3 - Boosting/5. AdaBoosting in R.mp4-88.68 MB
• 31. Project Creating CNN model from scratch/1. Project in R - Data Preprocessing.mp4-87.76 MB
• 23. Introduction - Deep Learning/4. Python - Creating Perceptron model.mp4-86.56 MB
• 14. Simple Classification Tree/5. Building a classification Tree in R.mp4-85.11 MB
• 26. ANN in R/5. ANN with NeuralNets Package.mp4-84.42 MB
• 6. Data Preprocessing/25. Correlation Matrix in R.mp4-83.14 MB
• 22. Creating Support Vector Machine Model in R/5. Polynomial Kernel with Hyperparameter Tuning.mp4-83.14 MB
• 3. Setting up R Studio and R crash course/3. Packages in R.mp4-82.94 MB
• 14. Simple Classification Tree/4. Classification tree in Python Training.mp4-82.71 MB
• 13. Simple Decision Trees/18. Pruning a Tree in R.mp4-82.09 MB
• 25. ANN in Python/7. Compiling and Training the Neural Network model.mp4-81.63 MB
• 16. Ensemble technique 2 - Random Forests/3. Using Grid Search in Python.mp4-80.66 MB
• 26. ANN in R/7. Complex Architectures using Functional API.mp4-79.57 MB
• 25. ANN in Python/6. Building the Neural Network using Keras.mp4-79.11 MB
• 7. Linear Regression/17. Subset selection techniques.mp4-79.06 MB
• 15. Ensemble technique 1 - Bagging/2. Ensemble technique 1 - Bagging in Python.mp4-77.31 MB
• 7. Linear Regression/15. Test-Train Split in R.mp4-75.6 MB
• 11. K-Nearest Neighbors classifier/4. K-Nearest Neighbors classifier.mp4-75.42 MB
• 17. Ensemble technique 3 - Boosting/6. Ensemble technique 3c - XGBoost in Python.mp4-75 MB
• 39. Time Series - ARIMA model/3. ARIMA model in Python.mp4-74.43 MB
• 10. Linear Discriminant Analysis (LDA)/3. Linear Discriminant Analysis in R.mp4-74.35 MB
• 11. K-Nearest Neighbors classifier/3. Test-Train Split in R.mp4-74.23 MB
• 13. Simple Decision Trees/17. Pruning a tree in Python.mp4-73.5 MB