# Titanic - Neural Network - Two hidden layers – 5 units ReLU and 3 units tanh **URL:** \ **Category:** ignite\ **Created:** [April 10, 2022, 7:10pm UTC](https://discuss.pytorch.org/t/titanic-neural-network-two-hidden-layers-5-units-relu-and-3-units-tanh/148761 "2022-04-10T19:10:33Z")\ **Posts on this page:** 4\ **Page:** 1
**Author:** ![dipakpatadia](https://discuss.pytorch.org/user_avatar/discuss.pytorch.org/dipakpatadia/32/48486_2.png) [@dipakpatadia](https://discuss.pytorch.org/u/dipakpatadia)\ **Post date:** [April 10, 2022, 7:10pm UTC](https://discuss.pytorch.org/t/titanic-neural-network-two-hidden-layers-5-units-relu-and-3-units-tanh/148761/1 "2022-04-10T19:10:33Z")
Want to build a model neural network model using **PyTorch** library. The model should use two hidden layers: the first hidden layer must contain **5 units using the ReLU** activation function; the second layer must contain **3 units using tanh** activation function. Want to use the Titanic train dataset I have. Want to use ONLY the train dataset (.CVV) and split the dataset (i.e., train.csv) to a training set (80% samples) and a testing set (20% samples) Don’t know how to define model definition for 2 hidden layers which are ReLU and tanh with 5 and 3 units (nucleus) respectively. A sample code would really help. Step by step code including standard methods implemented (data cleansing, normalizing, Model training, testing, etc.) would really help me to learn this. I am using a Jupyter notebook. Regards, Dipak ---
**Author:** ![ptrblck](https://discuss.pytorch.org/user_avatar/discuss.pytorch.org/ptrblck/32/1823_2.png) [@ptrblck](https://discuss.pytorch.org/u/ptrblck)\ **Post date:** [April 10, 2022, 8:52pm UTC](https://discuss.pytorch.org/t/titanic-neural-network-two-hidden-layers-5-units-relu-and-3-units-tanh/148761/2 "2022-04-10T20:52:12Z")
The [CIFAR10 tutorial](https://pytorch.org/tutorials/beginner/blitz/cifar10_tutorial.html) might be a good starter as it walks you through the data loading pipeline, defining a custom model, and training it. ---
**Author:** ![dipakpatadia](https://discuss.pytorch.org/user_avatar/discuss.pytorch.org/dipakpatadia/32/48486_2.png) [@dipakpatadia](https://discuss.pytorch.org/u/dipakpatadia)\ **Post date:** [April 11, 2022, 3:46am UTC](https://discuss.pytorch.org/t/titanic-neural-network-two-hidden-layers-5-units-relu-and-3-units-tanh/148761/3 "2022-04-11T03:46:38Z")
Thank you so much for referring good start. ---
**Author:** ![dipakpatadia](https://discuss.pytorch.org/user_avatar/discuss.pytorch.org/dipakpatadia/32/48486_2.png) [@dipakpatadia](https://discuss.pytorch.org/u/dipakpatadia)\ **Post date:** [April 13, 2022, 7:48am UTC](https://discuss.pytorch.org/t/titanic-neural-network-two-hidden-layers-5-units-relu-and-3-units-tanh/148761/4 "2022-04-13T07:48:45Z")
I am getting the below error. How this can be resolved? # Lets Split the Train Dataset into training set (80%) and Testing set (20%) X = train.drop(‘Survived’, axis=1).values y = train[‘Survived’].values X\_train, X\_test, y\_train, y\_test = train\_test\_split(X, y, test\_size=0.2, random\_state=42) X\_train = torch.FloatTensor(X\_train) X\_test = torch.FloatTensor(X\_test) y\_train = torch.LongTensor(y\_train) y\_test = torch.LongTensor(y\_test) TypeError Traceback (most recent call last) C:\Users\JAYPAT~1\AppData\Local\Temp/ipykernel\_5072/502746771.py in 6 X\_train, X\_test, y\_train, y\_test = train\_test\_split(X, y, test\_size=0.2, random\_state=42) 7 ----\> 8 X\_train = torch.FloatTensor(X\_train) 9 X\_test = torch.FloatTensor(X\_test) 10 y\_train = torch.LongTensor(y\_train) TypeError: can’t convert np.ndarray of type numpy.object\_. The only supported types are: float64, float32, float16, complex64, complex128, int64, int32, int16, int8, uint8, and bool.