In these tutorials, we will build our first Neural Network and try to build some advanced Neural Network architectures developed recent years.

All methods mentioned below have their video and text tutorial in Chinese. Visit 莫烦 Python for more.

• Tensorflow basic
  • Session
  • Placeholder
  • Variable
  • Activation
• Build your first network
  • Regression
  • Classification
  • Save and reload
  • Optimizers
  • Tensorboard
  • Dataset
• Advanced neural network
  • CNN
  • RNN-Classification
  • RNN-Regression
  • AutoEncoder
  • DQN Reinforcement Learning
  • GAN (Generative Adversarial Nets) / Conditional GAN
  • Transfer Learning
• Others (WIP)
  • Dropout
  • Batch Normalization
  • Visualize Gradient Descent
  • Distributed training

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双均线指标代码： //@version=4 study(title="均线系统", shorttitle="均", overlay = true ) sma20 = sma(close,20) sma60 = sma(close,60) sma120 = sma(close,120)

ema20 = ema(close,20) ema60 = ema(close,60) ema120 = ema(close,120)

plot(sma20,color=color.black,title="SMA20") plot(ema20,color=color.new(color.black,50),title="EMA20")

plot(sma60,color=color.blue,title="SMA60") plot(ema60,color=color.new(color.blue,50),title="EMA60")

plot(sma120,color=color.purple,title="SMA120") plot(ema120,color=color.new(color.purple,50),title="EMA120")

cond=barstate.islast bl=low moveBar = input(0) x20=input(20)+moveBar x60=input(60)+moveBar x120=input(120)+moveBar plot(cond?bl[20]:na,color= #FFC40C,linewidth=5,offset=-x20,style=plot.style_circles,transp=0) plot(cond?bl[60]:na,color= #FFC40C,linewidth=5,offset=-x60,style=plot.style_circles,transp=0) plot(cond?bl[120]:na,color= #FFC40C,linewidth=5,offset=-x120,style=plot.style_circles,transp=0)