Update UPDATES.md

UPDATES.md

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 # Update Log
 
+### Update 0.3.10 - 03.28.2021
+- Support **Genetic Algorithm** officially. 
+- **BLAS** is now running with a single thread in default. 
+- Fixed a few bugs. 
+
+### Update 0.3.9 - 03.15.2021
+- Updated the API and it can now auto-complete most of the parameters. 
+- Added **padding** and **biases** in **Conv2D**. 
+- Added **UpSampling2D** as a layer. 
+- Added **Genetic Algorithm** as an experimental optimizer. 
+- Fixed a few bugs. 
+
 ### Update 0.3.8 - 02.24.2021
-- Fix that the speed of convergence for training convolutional networks is slower as expected. (Except with **Minibatch_GD**, I suppose this optimizer is just inefficient in this case. )
+- Fixed that the speed of convergence for training convolutional networks is slower as expected. (Except with **Minibatch_GD**, I suppose this optimizer is just inefficient in this case. )
 - Support **HDF5.jl** 0.15.4
 
 ### Update 0.3.7 - 02.22.2021
-- Add a limit of interval **(-3.0f38, 3.0f38)** for value to prevent overflow and **NaN**. 
+- Added a limit of interval **(-3.0f38, 3.0f38)** for value to prevent overflow and **NaN**. 
 - **GAN** can now display the loss of discriminator. 
-- Sightly improve the sytax. 
+- Sightly improved the sytax. 
 
 ### Update 0.3.6 - 02.20.2021
-- Add **GAN** as a new type of networks. 
-- Split **Cross_Entropy_Loss** to **Categorical_Cross_Entropy_Loss** and **Binary_Cross_Entropy_Loss**. 
-- Fix the loss display of **AdaBelief**. 
+- Added **GAN** as a new type of networks. 
+- Split **Cross_Entropy_Loss** into **Categorical_Cross_Entropy_Loss** and **Binary_Cross_Entropy_Loss**. 
+- Fixed the loss display of **AdaBelief**. 
 - Known issues: there is a possibility to produce **NaN**, I am still working on it. For now, reduce the usage of **ReLU** in relatively deep networks may solve the problem. 
 
 ### Update 0.3.5 - 02.19.2021
-- Fix that **AdaBelief** activates **Adam**. 
-- Optimize the structure for development of **GAN** model in the future. 
-- Update the argument keywords for `fit` function. 
+- Fixed that **AdaBelief** activates **Adam**. 
+- Optimized the structure for development of **GAN** model in the future. 
+- Updated the argument keywords for `fit` function. 
 
 ### Update 0.3.4 - 02.14.2021
-- Greatly improve the training speed by optimizing the structure. 
-- Fix that the filters in **Conv2D** cannot be updated until saved. 
-- Fix that the model cannot by trained multiple times. 
+- Greatly improved the training speed by optimizing the structure. 
+- Fixed that the filters in **Conv2D** cannot be updated until saved. 
+- Fixed that the model cannot by trained multiple times. 
 
 ### Update 0.3.2 - 02.12.2021
-- Add **SGD** as an optimizer.
-- Optimize the structure and sytax, the "minibatch" problem is now solved. 
-- Accelerate the framework by using [LoopVectorization.jl](https://github.com/chriselrod/LoopVectorization.jl).
+- Added **SGD** as an optimizer.
+- Optimized the structure and sytax, the "minibatch" problem is now solved. 
+- Accelerated the framework by using [LoopVectorization.jl](https://github.com/chriselrod/LoopVectorization.jl).
 - Use GlorotUniform to generate random weights and biases. 
 
 ### Update 0.2.6 - 02.06.2021
-- Add **Monitor** to show the current loss
+- Added **Monitor** to show the current loss
 - Known issues: I find out that all my optimizers update once after a batch, that means they work just like **Minibatch Gradient Descent**, so **Adam** and **AdaBelief** are not working properly but like **Minibatch Adam** and **Minibatch AdaBelief**. This slows down the training process. I will try to reconstruct the whole program in the next update. 
 
 ### Update 0.2.5 - 02.02.2021
-- Greatly imporve the training speed.
+- Greatly improved the training speed.
 - In the example, it is about 20 seconds slower than Keras (epochs=5, batch_size=128). 
 
 ### Update 0.2.4 - 01.28.2021
-- Add **Convolutional2D** and **MaxPooling2D** as layers.
-- Add **Mean Squared Loss** as a loss function.
-- Add **Adam** and **AdaBelief** as optimizers.
-- Add **One Hot** and **Flatten** as tools.
-- Improve the structures.
-- The code is now completely in Julia. 
+- Added **Convolutional2D** and **MaxPooling2D** as layers.
+- Added **Mean Squared Loss** as a loss function.
+- Added **Adam** and **AdaBelief** as optimizers.
+- Added **One Hot** and **Flatten** as tools.
+- Improved the structures.
 - Known issues: Convolutional2D requires a lot of RAM and is relatively slow. 
-
-### Update 0.1.1 - 05.12.2020
-- Add **tanh** as an activation function.
-- Add **model management** in tools and can save and load models.
-- Improve the syntax slightly.
-- This would be the last Python version of this framework. I am re-programming this project in Julia.