Alzheimer’s disease is a neurological condition marked by alterations in the brain that result in the accumulation of specific proteins. This accumulation leads to the shrinking of the brain and eventual death of brain cells, loses functioning of neurons, connection with other neurons and eventually die. Alzheimer’s disease is the primary cause of dementia, which manifests as a progressive decline in cognitive functions like memory, reasoning, behavior, and social interactions. These changes significantly impact an individual’s daily functioning. At first, Alzheimer’s disease targets the areas of the Brain responsible for/involved in memory, including the entorhinal cortex and hippocampus. It later affects the areas present in the cerebral cortex responsible for language, reasoning and social behavior. Due to the brain losing functionality by eventual death of brain cells, neurons stop working throughout the brain and the neural connections or the neural networks break down. This process is called Brain Atrophy, resulting from significant cellular death and causing the loss of Brain in volume. The suggested approach utilizes Machine learning and Deep learning algorithms to process brain MRI-scans. The aim of proposed work is to portray/visualize the output through GRAD-CAM and OCCLUSION SENSITIVITY MAPPING to identify and visualize the targeted brain areas and display them after each convolution layer. The suggested method has many benefits over the conventional models.