Update README.md

Author: khuyentran1401

README.md

@@ -111,7 +111,7 @@ git-lfs clone https://github.com/khuyentran1401/Data-science
 | Title        | Article           | Repository  |
 | ------------- |:-------------:| :-----:|
 | How to Monitor And Log your Machine Learning Experiment Remotely with HyperDash | [🔗](https://towardsdatascience.com/how-to-monitor-and-log-your-machine-learning-experiment-remotely-with-hyperdash-aa7106b15509) | [🔗](https://github.com/khuyentran1401/Data-science/tree/master/data_science_tools/Hyperdash.ipynb) |
-|How to Efficiently Fine-Tune your Machine Learning Models | <a href="https://towardsdatascience.com/how-to-fine-tune-your-machine-learning-models-with-ease-8ca62d1217b1" target="_blank">link</a>| [🔗](https://github.com/khuyentran1401/Machine-learning-pipeline) |
+|How to Efficiently Fine-Tune your Machine Learning Models | [🔗](https://towardsdatascience.com/how-to-fine-tune-your-machine-learning-models-with-ease-8ca62d1217b1) | [🔗](https://github.com/khuyentran1401/Machine-learning-pipeline) |
 | How to Learn Non-linear Dataset with Support Vector Machines | [🔗](https://towardsdatascience.com/how-to-learn-non-linear-separable-dataset-with-support-vector-machines-a7da21c6d987) | [🔗](https://github.com/khuyentran1401/Data-science/tree/master/machine-learning/SVM_Separate_XOR.ipynb) |
 | Introduction to IBM Federated Learning: A Collaborative Approach to Train ML Models on Private Data | [🔗](https://towardsdatascience.com/introduction-to-ibm-federated-learning-a-collaborative-approach-to-train-ml-models-on-private-data-2b4221c3839) | [🔗](https://github.com/IBM/federated-learning-lib)
 | 3 Steps to Improve your Efficiency when Hypertuning ML Models | [🔗](https://towardsdatascience.com/3-steps-to-improve-your-efficiency-when-hypertuning-ml-models-5a579d57065e)