Hello Guys, How are you all? Hope You all Are Fine. Today I get the following error **(Keras) ValueError: Failed to convert a NumPy array to a Tensor (Unsupported object type float)** in** Python**. So Here I am Explain to you all the possible solutions here.

Without wasting your time, Let’s start This Article to Solve This Error.

Table of Contents

## How (Keras) ValueError: Failed to convert a NumPy array to a Tensor (Unsupported object type float) Error Occurs?

Today I get the following error **(Keras) ValueError: Failed to convert a NumPy array to a Tensor (Unsupported object type float)** in** Python**.

## How To Solve (Keras) ValueError: Failed to convert a NumPy array to a Tensor (Unsupported object type float) Error ?

**How To Solve (Keras) ValueError: Failed to convert a NumPy array to a Tensor (Unsupported object type float) Error ?**To Solve (Keras) ValueError: Failed to convert a NumPy array to a Tensor (Unsupported object type float) Error Could also happen due to a difference in versions (I had to move back from tensorflow 2.1.0 to 2.0.0.beta1 in order to solve this issue).

**(Keras) ValueError: Failed to convert a NumPy array to a Tensor (Unsupported object type float)**To Solve (Keras) ValueError: Failed to convert a NumPy array to a Tensor (Unsupported object type float) Error Could also happen due to a difference in versions (I had to move back from tensorflow 2.1.0 to 2.0.0.beta1 in order to solve this issue).

## Solution 1

After trying everything above with no success, I found that my problem was that one of the columns from my data had `boolean`

values. Converting everything into `np.float32`

solved the issue!

import numpy as np X = np.asarray(X).astype(np.float32)

## Solution 2

Could also happen due to a difference in versions (I had to move back from tensorflow 2.1.0 to 2.0.0.beta1 in order to solve this issue).

**Summery**

It’s all About this issue. Hope all solution helped you a lot. Comment below Your thoughts and your queries. Also, Comment below which solution worked for you? Thank You.

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