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    [CS 297 Proposal]

    [Comparison between hash2vec and word2vec -pdf]

    [Different Approaches for word2vec from reference paper -pdf]

    [Deliverable 1]

    [Deliverable 2]

    [Deliverable 3]

    [Deliverable 4]

    [Deliverable 5]


    [CS 298 Proposal]



we tried to test the vectors produced in previous deliverable i.e. hash2vec vectors to calculate their distance by using euclidean distance formula. Lets get some insights about euclidean distance first and then see details about its implementation in this deliverable. The Euclidean distance between the points p and q is the length of the line segment connecting them[9].if p = (p1, p2,..., pn) and q = (q1, q2,..., qn) are two points in Euclidean n-space, then the distance (d) from p to q, or from q to p is given by the below formula.