def get_embedded_matrix(max_words,embedding_dim,vocab,embeddings_index):
    counter = 0
    total_ct = 0
    embedding_matrix = np.zeros((max_words, embedding_dim))
    for word,index in vocab.items():
        total_ct += 1
        embedding_vector = embeddings_index.get(word)
        if embedding_vector is not None:
            embedding_matrix[index] = embedding_vector
            counter += 1
        else:
            embedding_matrix[index] = np.random.uniform(-0.25, 0.25, embedding_dim)
    print('Total ',total_ct,' gasit ',counter)
    return embedding_matrix