Update README.md

README.md

@@ -22,15 +22,23 @@ Recent developments in Quantum Computing (QC) have paved the way for an enhancem
 
 👌 Everyone can make a free account to run on the D-Wave Advantage quantum annealer: 
 
-- Make a free account to run on the D-Wave through 👉 (https://www.dwavesys.com/take-leap
+- Sign up on D-Wave Leap through 👉 https://www.dwavesys.com/take-leap
 
 - Install Ocean Software with 'pip install dwave-ocean-sdk' 👉 https://docs.ocean.dwavesys.com/en/latest/overview/install.html
 
-- Configuring the D-Wave System as a Solver with 'dwave config create' 👉 https://docs.ocean.dwavesys.com/en/stable/overview/sapi.html
+- Configure the D-Wave System as a Solver with 'dwave config create' 👉 https://docs.ocean.dwavesys.com/en/stable/overview/sapi.html
+
+- Check the available computing time for your account on the D-Wave Leap Dashboard 👉 https://cloud.dwavesys.com/leap/login/
 
 ### IBM Quantum Experience
 
+👌 Everyone can make a free account to run on IBM quantum machines and simulators: 
+
+- Sign up and login on IBM Quantum Experience through 👉 https://quantum-computing.ibm.com/login
+
+- Install Qiskit with 'pip install qiskit' 👉 https://qiskit.org/documentation/getting_started.html
 
+- In a notebook, configure the provider using your personal token 👉  https://quantum-computing.ibm.com/lab/docs/iql/manage/account/ibmq
 
 ## Experiments
 
@@ -55,7 +63,7 @@ Test set:
 
 ### Classification with classical SVM (Scikit-Learn)
 
-Follow the instructions of the Jupyter Notebook 👉
+Follow the instructions of the Jupyter Notebook 👉 experiments/Classic_SVM/Classic_SVM.ipynb
 
 ### Classification with QA-based QSVM (D-Wave QA)
 
@@ -63,7 +71,7 @@ Follow the instructions of the Jupyter Notebook 👉 experiments/QA_SVM/QA_SVM.i
 
 ### Classification with Circuit-based QSVM (IBM Quantum Experience)
 
-Follow the instructions of the Jupyter Notebook 👉
+Follow the instructions of the Jupyter Notebook 👉 experiments/Circuit_SVM/Circuit_SVM.ipynb
 
 ## Support