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365 Data Science - Deep Learning with TensorFlow [CoursesGhar]

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English

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2.51 GB

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28-06-2021 19:12

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File	Size
!! IMPORTANT Note !!.txt	298.00 B
!!! Please Support !!! [CoursesGhar.Com].txt	197.00 B
00. Websites You May Like/A1movies.com.pk.url	116.00 B
00. Websites You May Like/CoursesGhar.com.url	114.00 B
1. Introduction/1. Welcome to Machine Learning.mp4	37.95 MB
1. Introduction/2. What does the course cover.mp4	49.21 MB
10. Optimizers/1. SGD_Batching.mp4	34.48 MB
10. Optimizers/2. Local minima pitfalls.mp4	14.35 MB
10. Optimizers/3. Momentum.mp4	18.96 MB
10. Optimizers/4. Learning rate schedules.mp4	37.08 MB
10. Optimizers/5. Learning rate schedules. A picture.mp4	10.93 MB
10. Optimizers/6. Adaptive learning schedules.mp4	29.83 MB
10. Optimizers/7. Adaptive moment estimation.mp4	29.08 MB
11. Preprocessing/1. Preprocessing.mp4	25.55 MB
11. Preprocessing/2. Basic preprocessing.mp4	11.11 MB
11. Preprocessing/3. Standardization.mp4	40.37 MB
11. Preprocessing/4. Dealing with categorical data.mp4	18.22 MB
11. Preprocessing/5. One-hot vs binary.mp4	32.26 MB
12. Deeper example/1. MNIST dataset.mp4	8.53 MB
12. Deeper example/2. How to tackle the MNIST dataset.mp4	30.94 MB
12. Deeper example/3. MNIST - Importing libraries and data.mp4	12.71 MB
12. Deeper example/4. MNIST - Outlining the model.mp4	44.99 MB
12. Deeper example/5. MNIST - Declaring the loss.mp4	18.71 MB
12. Deeper example/6. Accuracy of a model.mp4	40.20 MB
12. Deeper example/7. Early stopping and batching preparation.mp4	9.87 MB
12. Deeper example/8. Optimization.mp4	34.04 MB
12. Deeper example/9. Commenting on the results.mp4	52.76 MB
13. Business case/1. The dataset.mp4	52.62 MB
13. Business case/10. Homework.mp4	57.49 MB
13. Business case/2. Outlining the solution.mp4	12.11 MB
13. Business case/3. Balancing a dataset.mp4	44.95 MB
13. Business case/4. Preprocessing the data.mp4	78.73 MB
13. Business case/5. Creating the batching class.mp4	56.65 MB
13. Business case/6. Outlining the model.mp4	46.28 MB
13. Business case/7. Optimizing the algorithm.mp4	27.49 MB
13. Business case/8. Running the code.mp4	19.90 MB
13. Business case/9. Test.mp4	8.84 MB
14. Conclusion/1. Summary.mp4	48.54 MB
14. Conclusion/2. Whats more out there.mp4	17.51 MB
14. Conclusion/3. An overview of CNNs.mp4	71.95 MB
14. Conclusion/4. An overview of RNNs.mp4	27.42 MB
14. Conclusion/5. Non-NN approaches.mp4	41.90 MB
2. Neural networks Intro/1. Introduction to neural networks.mp4	42.58 MB
2. Neural networks Intro/10. Cross-entropy loss.mp4	33.40 MB
2. Neural networks Intro/11. One-parameter gradient descent.mp4	56.41 MB
2. Neural networks Intro/12. N-parameter gradient descent.mp4	50.04 MB
2. Neural networks Intro/2. Training the model.mp4	26.82 MB
2. Neural networks Intro/3. Types of machine learning.mp4	40.85 MB
2. Neural networks Intro/4. The linear model.mp4	26.04 MB
2. Neural networks Intro/5. The linear model. Multiple inputs..mp4	23.69 MB
2. Neural networks Intro/6. The linear model. Multiple inputs and multiple outputs.mp4	42.21 MB
2. Neural networks Intro/7. Graphical representation.mp4	21.96 MB
2. Neural networks Intro/8. The objective function.mp4	17.70 MB
2. Neural networks Intro/9. L2-norm loss.mp4	21.40 MB
3. Setting up the environment/1. Setting up the environment - Do not skip, please!.mp4	7.92 MB
3. Setting up the environment/2. Why Python and why Jupyter.mp4	34.66 MB
3. Setting up the environment/3. Installing Anaconda.mp4	37.10 MB
3. Setting up the environment/4. Jupyter Dashboard - Part 1.mp4	10.32 MB
3. Setting up the environment/5. Jupyter Dashboard - Part 2.mp4	21.00 MB
3. Setting up the environment/6. Installing the TensorFlow package.mp4	14.13 MB
4. Minimal example/1. Outline.mp4	13.94 MB
4. Minimal example/2. Generating the data (optional).mp4	23.74 MB
4. Minimal example/3. Initializing the variables.mp4	20.43 MB
4. Minimal example/4. Training the model.mp4	46.57 MB
5. Introduction to TensorFlow/1. TensorFlow outline.mp4	44.62 MB
5. Introduction to TensorFlow/2. TensorFlow introduction.mp4	19.31 MB
5. Introduction to TensorFlow/3. Types of file formats used in TensorFlow.mp4	12.90 MB
5. Introduction to TensorFlow/4. Laying down the model.mp4	27.71 MB
5. Introduction to TensorFlow/5. Laying down the optimizers.mp4	21.45 MB
5. Introduction to TensorFlow/6. Output.mp4	30.23 MB
6. Deep nets overview/1. The layer.mp4	16.36 MB
6. Deep nets overview/2. What is a deep net.mp4	32.60 MB
6. Deep nets overview/3. Really understand deep nets.mp4	58.18 MB
6. Deep nets overview/4. Why do we need non-linearities.mp4	37.97 MB
6. Deep nets overview/5. Activation functions.mp4	29.18 MB
6. Deep nets overview/6. Softmax activation.mp4	24.98 MB
6. Deep nets overview/7. Backpropagation.mp4	52.73 MB
6. Deep nets overview/8. Backpropagation - intuition.mp4	24.39 MB
8. Overfitting/1. Underfitting and overfitting.mp4	34.06 MB
8. Overfitting/2. Underfitting and overfitting. A classification example.mp4	32.48 MB
8. Overfitting/3. Train vs validation.mp4	37.52 MB
8. Overfitting/4. Train vs validation vs test.mp4	31.32 MB
8. Overfitting/5. N-fold cross validation.mp4	25.57 MB
8. Overfitting/6. Early stopping - motivation and types.mp4	28.33 MB
9. Initialization/1. Initializaiton.mp4	26.17 MB
9. Initialization/2. Types of simple initializations.mp4	12.29 MB
9. Initialization/3. Xavier_s initialization.mp4	19.12 MB
Join Our Telegram Group For More Updates !!!.url	138.00 B
Uploaded by [Coursesghar.com].txt	1.10 kB
Visit coursesghar.com for more awesome tutorials.url	114.00 B

Description

365 Data Science - Deep Learning with TensorFlow [CoursesGhar]

Course description

Machine and deep learning are some of those quantitative analysis skills that differentiate the data scientist from the other members of the team. The field of machine learning is the driving force of artificial intelligence. This course will teach you how to leverage deep learning and neural networks from this powerful tool for the purposes of data science. We will be doing this with TensorFlow.